task9.jsonl

{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The survey data were collected by Energy Institute at the Johannes Kepler University Linz, following high European Union standards of data protection and voluntary study participation. The methodology used in this paper does not require institutional ethical approval according to the guidelines set out by the Energy Institute at the Johannes Kepler University Linz. Confidentiality and anonymity of participants was ensured and informed written consent was obtained from all the interviewees.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 0}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To cover the range of potential network tariff schemes, we designed a total number of 11 scenarios. First, we designed one respective tariff scenario recovering the network costs through only one of the three components\u2014volume, fixed charge and measured peak load (average and maximum). Scenario f100 is a 100% fixed charge. Thereby, f100 represents a flat charge for all households, which is \u20ac 136,209.10 / 765 households =\u20ac 178.05 per household per year for the full sample in our study. Scenario pa100 represents a scheme charging for measured peak load only. In this scenario, the definition of kW peak load follows the Austrian tariff structure in 201648, where a so-called smart meter tariff was included for testing only (in the residential sector). There, kW peak load as relevant for billing is not defined as  the one maximum load out of the 35,040 metered load values during one year  per Austrian meter. Peak load as relevant for setting a household's peak charge  is defined as the average of the 12 monthly peak loads during the respective  year. Scenario pa100 for the full sample analysis therefore sets  \u20ac 136,209.10 / 3,485.59 kW total =\u20ac 39.07 per kW of billing relevant peak load, where kW total is the sum over all 765 corresponding peak-load values. Scenario pm100 also represents a scheme charging for peak demand only, but instead of averaging, the highest of the 12 monthly peaks is applied, such that it sets \u20ac 136,209.10 / 4,603.3 kW total =\u20ac 29.59 per kW of billing relevant peak load, where kW total is the sum over all 765 corresponding peak-load values. Scenario e100 is a fully volumetric tariff and includes only a payment  per unit of consumed energy. Thereby it is \u20ac 136,209.10 / 2,691,272 kWh total = \u20ac 0.0506 per kWh consumed during the respective year, where kWh total is  the aggregated electricity consumption of all 765 households.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 1}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To help address some of these potential confounders, standard multiple regression techniques would introduce controls to adjust for consequential observable differences between diagnosed and undiagnosed children. However, standard controls within OLS regressions may not be adequate if there is insufficient overlap, or balance, in the distributions of characteristics between diagnosed and undiagnosed children (Imbens and Rubin 2015). Researchers have turned to matching techniques to help achieve sample balance on key variables for which OLS models may yield estimates that lack sample support/balance (Gangl 2010). This study used two types of matching to obtain estimates that are \u201cdoubly robust\u201d to confounding between diagnosed and undiagnosed children: coarsened exact matching (CEM) and propensity score matching (PSM) (Stuart et al. 2009). First, I use CEM to preprocess the data and ensure sample balance on three key factors that shape both diagnosis and the outcomes: family social class group (given the study's theoretical motivation), severity quartile of prediagnosis behavioral problems (a key confounder of diagnostic effects), and child sex (since sex differences in children's presentation of ADHDrelated behaviors could produce improper matches given greater diagnosis of the hyperactive subtype among boys).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 2}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used data of electrolysis project announcements from the IEA Hydrogen Production Projects and Infrastructure Database58 (previously called the IEA Hydrogen Projects Database), incorporating three database snapshots from 2021, 2022 and 2023. We only included project announcements for electrolysers that included a year of project launch, had a meaningful status (not 'Other' or 'Other/Unknown') and reported a capacity value. We did not filter for the type of electricity as this was often unknown. These criteria led to 612 projects in the 2021 snapshot, 877 projects in the 2022 snapshot and 1,265 projects in the 2023 snapshot. In the 2023 snapshot, only a single status category was reported for projects that were either under construction or had an FID ('FID/Construction'). To ensure consistent status categories across all snapshots, we merged the 'FID' and 'Under construction' categories in the 2021 and 2022 snapshots. Projects with a 'DEMO' status were allocated as 'Operational', 'FID/Construction' or 'Decommissioned', depending on whether they were still running, announced for the future or had been decommissioned, respectively. We note that the 'Concept' category is very broadly defined with an unspecified credibility bar for inclusion, while the 'Feasibility study' category may also contain projects for which a feasibility study is planned, but has not yet started. Confidential projects were distributed to all regions in proportion to the share of capacity from non-confidential projects, but could not be tracked across database snapshots.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 3}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The economic dispatch (ED) problem was formulated as a convex quadratic program, the outcome of which depends on the realization of the random variables that govern demand, availability and fuel costs. The problem splits operations into simple time blocks of varying length, which reflect the different levels of load seen throughout the year without explicitly representing operational considerations, such as unit commitment decisions, which in general preclude equilibria, or ramping constraints, which can exacerbate the issue of multiple equilibria. In general, the inclusion of these constraints leads to a greater need for capacity, but their implications for the resource mix are not well understood48.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 4}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We collected data on private funding from three sources: Thomson ONE, Crunchbase and Preqin. To obtain the total funding received by a company at the end of a given calendar year, we use the maximum amount recorded from any of the three sources. We limited our observations to funding deals announced between January 1, 2004, and December 31, 2017. For VC funding, we include the following deal types: Venture Capital Equity Investment (Thomson ONE); Seed, Series A-I, Venture\u2014Series Unknown (Crunchbase); and Seed, Series A-I (Preqin). For private funding variables, we include all VC funding deals, plus the following deal types as well: Common Stock, Convertible Preferred Stock, Preferred Shares and Warrants (Thomson ONE); Angel, Convertible Note, Corporate Round, Equity Crowdfunding, Funding Round, Post-IPO Equity, Pre-Seed and Private Equity (Crunchbase); Add-on, Angel, Growth Capital/Expansion, Private Investment in Public Equity (PIPE) and Unspecified Round (Preqin).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 5}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We examined four dependent variables: (1) preterm birth (binary, <37 completed weeks gestation), (2) low birthweight (binary, <2500 grams), (3) birthweight (continuous, grams), and (4) entry into prenatal care in the first trimester (binary, entered in first three months). We measured gestational age in weeks using the combined last menstrual period and physical estimated gestational age variable (Dietz  et al. 2014).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 6}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    For each water extraction, the smart shower meter recorded energy and water consumption, average water temperature, interruptions and the duration. In addition, in 168 of the rooms, the average flow rate per shower was also measured. Using the data stored on the device, energy consumption can be converted to water consumption and vice versa. Given the high correlation between water and energy consumption per shower (0.989)25, the choice of the unit of analysis does not change the results in any meaningful way. This article focuses on resource consumption in units of energy in kilowatt hours. The raw data set included observations of 25,647 measured showers from 269 hotel rooms at 6 different hotels (see Data availability). In a first pre-processing step, the data were cleaned by removing outliers from malfunctioning devices; to this end, observations that deviated by over 3 standard deviations from the mean  of the energy consumed or water volume per shower were removed from the  sample\u2014that is, only observations in the interval [ -x . . + x . . x x 3 sd, 3 sd ] were retained. Furthermore, we removed data points that most likely did not represent showers\u2014for example water extractions of volumes below 6.5 litres and observations deviating over 2 standard deviations from average temperature, which probably represent cleaning or other procedures. A member of the research team accompanied cleaning personnel at one hotel for several hours to gather information on cleaning practices to identify water extractions for cleaning. The specific choice of 6.5 litres was based on this assessment; we conducted robustness checks in which we changed this threshold to other values (5 litres or 10 litres), which generated very similar results. After this pre-processing step, the final data set included 19,596 showers from 265 hotel rooms (11,384 observations in the treatment group and 8,218 in the control group). The average flow rate per shower could be measured only for 168 rooms and 8,824 observations, so only these data points are included in the estimation of models (2) and (3) in Table 2. Since the study is a natural field experiment with uninformed participants, we were not able to collect socio-demographic data about the guests who stayed in the rooms with the smart shower meters during the study.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 7}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Subscriptions are classified as with and without intent to control deforestation. We exclude subscriptions for areas greater than 100 Mha (this area corresponds to a little more than the size of a large state (such as Mato Grosso, Brazil) or a small country (Portugal for example) as they are considered too large to be used for monitoring and are most probably associated with users exploring the platform. To create the with-intent group, we exclude all subscriptions associated with the academic sector as well as those subscriptions created by staff from WRI or affiliates (together these constitute the without-intent subscriptions). The end result is a total of 558 subscriptions with intent and 734 without. The number of grid cells ever covered by a subscription with intent is 399,660, whereas those that have ever been covered by a subscription without intent total 298,574. Of the 558 subscriptions with intent, 302 declared their primary job responsibility using a drop down menu within the alerts system. Supplementary Table B22 details these responses. The majority of these were GIS specialists, with a relatively large number of programme managers, technical staff, land-use planning specialist, reporters, and forest/park managers. Of those that did not answer this question but did declare their location, the largest number was from Indonesia. The subscriptions layer has time and spatial variation. Each polygon of the layer corresponds to a subscribed area with a date of initiation of the subscription. Although it is the case that some subscribers terminate their subscriptions, to circumvent the potential endogeneity problems with using this variation, we assume that once a subscription has been made, the user remained interested in  the subscribed area until the end of our study period. Grid cells are marked as  with subscription from the date of the first subscription.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 8}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The samples are based on quota criteria. That is, the probability for each individual who could theoretically be included is not determined in advance but is based on their demographic background information, such as gender, age and region, from population statistics/census from each country. Respondents participating in the study were randomly exposed to different kinds of policy measures (treatments). They did not know the treatment group to which they had been assigned. Subsequent to the question on policy support, they were asked to state their evaluative response to the specific policy. The respondents also answered survey questions regarding their gender, age, educational background, household income level, area of residence and climate concern.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 9}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We performed preprocessing of the LL84 dataset prior to our analysis. First, as EUI data are self-reported, we identified and removed misreported and erroneous entries. Specifically, we applied a logarithmic transformation to the EUI data and filtered outlier values that fell outside the threshold of two standard deviations from the mean58. Second, using the unique Borough Block Lot property identifier, we merged energy and building attribute data with tax lot and zoning information provided by the NYC's Primary Land Use Tax Lot Output database to identify additional building characteristics, such as assessed value. Finally, we integrated NATure eNergYthe merged dataset with information from individual audit reports submitted to the Department of Buildings as per LL87 requirements to identify properties that conducted an energy audit in calendar years 2013 or 2014, and to analyse buildingspecific ECM recommendations and savings potentials.After our data processing steps, we analysed whether the audited properties in our sample demonstrated larger percentage reductions in site EUI between the pre- and postaudit period than those of similar buildings that did not perform an audit during the study period. We defined the EUI percentage change for each building as the difference between the mean EUI during the two years prior to the audit (2011 and 2012) and the two years after the audit (2015 and 2016). We used the two-year average to account for anomalous variations in building energy consumption that could occur in a given year (for example, Hurricane Sandy had a non-trivial impact on energy use in buildings in the impacted areas in 2012). We focused on multifamily and office buildings, as the two types account for more than 90% of the total LL84 covered properties by quantity and aggregate energy consumption. The merged dataset contains 3,981 properties, which include 3,563 multifamily buildings and 418 office buildings.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 10}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our analytical strategy utilized regression models with fixed effects for states and years. Fixed effects control for omitted variables that are time-invariant by examining variability within states rather than between states. We used the xtreg command in Stata along with the fe option to estimate regression models with fixed effects for years and states, with robust standard errors clustered by state. The time fixed effects were accounted for by the inclusion of yearspecific intercepts. Linear models with fixed effects assume linear additive effects. All models accounted for serial correlation using the vce (robust) command in Stata. In the tables and text, we provide coefficients, their uncertainty (standard errors or confidence intervals), and p value thresholds up to .10 to improve transparency and reproducibility of our results (Wasserstein and Lazar 2016).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 11}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used a subsample of n = 4,129 households that were assigned to TOU (not control) and did not answer \u201cNot applicable\u201d when asked about AC curtailment (that is, we only considered households that have access to AC in their homes). Only households assigned to TOU were examined to restrict the comparison to households with the incentive to curtail during peak hours. For this subsample, we examined whether the vulnerable or non-vulnerable groups reported more frequent curtailment in the form of AC use. We used Wilcoxon rank sum tests (due to non-normal distributions) to test for differences in the reported frequency of evening AC curtailment among vulnerable versus non-vulnerable households. Table 4 reports the means, z scores with associated P tests and Cohen's d effect sizes (d). Effect sizes indicate the importance of mean differences; a large effect size is >0.8, a medium one >0.5 and a small one >0.2 (ref. 61). The results provide a richer description of how households responded to TOU rates, and are correlational rather than causal.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 12}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used data from the 2021 EBA transparency exercise, which provides portfolio-level information of banks' gross exposure and accumulated provisions (LLR) by NACE sector level 1 at the end of June 2021. We used the  most recent data, but with additional robustness analysis, ensured that the results do not change using different years (the reader should note that due to the structure of this modelling, the provision coverage ratios oscillate with time in level but the relative difference across sectors is generally preserved). NACE is a standard classification of sectors in the European Union. It has various levels of granularity from 1 (least granular) to 4 (most granular), and the EBA transparency exercise relies on this classification. The exercise is an annual data collection to foster transparency and to complement banks' own disclosures. The data published includes 111 EU banks across 25 countries and provides information regarding banks' assets, liabilities, loan loss provisions and other financial information for each bank.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 13}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Final energy demands for the different sectors are calculated based on the JRC IDEES database123 with additions for non-EU countries (refs. 10,60 provide further elaboration) and need to be met (that is, demand is perfectly inelastic). However, energy carrier production including electricity, hydrogen, methane and liquid fuels is determined . Fossil fuels (coal, natural gas and oil) and uranium are included, as are solid biomass imports as outlined below. Technology costs and efficiencies are elaborated on in the Supplementary Information, with technology values for 2040 (given in \u20ac2015) used from the PyPSA energy system technology data set v0.6.0 (ref. 124). The discount rate is uniform across countries and set to 7%, except for rooftop solar PV and decentral space/water heating technologies, for which it is set to 4%.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 14}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Mothers' reports of baseline education were coded into one of four categories: less than a high school degree, high school degree/ General Education Development (GED), some college, bachelor's or higher. Unfortunately, the baseline reports did not differentiate mothers with \u201csome college\u201d from those with an associate's degree. It did distinguish mothers with a technical/trade degree, although this group was small (6% of the sample). Thus, mothers with technical/trade degrees were included in the \u201csome college group,\u201d but I did use this information in models that restrict the sample based on mothers' baseline education (explained in the following). At each follow-up wave, women reported whether they had earned a higher education degree among a variety of institution types (e.g., technical degree, secretarial school, associate's degree, etc.) since the last interview. Using this information, I created three time-varying, binary variables for completed a vocational program, completed an associate's degree, and completed a bachelor's degree. Once mothers reported degree completion, mothers were assigned a value of 1 on that measure for all subsequent waves. This coding technique captured a pooled estimate of the association between additional education and health that used all available data and provided an average of mothers' health before versus after completing additional education. Mothers were also asked if they had enrolled in school since the last interview, but only where they had enrolled during Waves 2 to 5. I used this information to create a parallel set of bivariate measures of enrolled in a vocational program, enrolled in an associate's program, and enrolled in a bachelor's degree program for ancillary analyses exploring the impact of school enrollment (restricted to Waves 2-5).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 15}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We use a set of variables to control for socio-economic factors that are likely to impact regular use of LPG by rural households, and include state-level fixed effects to account for variation in unspecified state-level factors that could affect household consumption of LPG48,64. Supplementary Table 10 (cross-section subset) and Supplementary Table 11 (panel subset) also contain descriptive summaries of all control variables, along with the hypothesized direction of association between the covariate and LPG-use category.We utilize an economic status index as a measure of a household's relative wealth and economic status, based on the Filmer and Pritchett65 approach. Such indices are commonly used across studies in regions where fixed incomes are uncommon65-67. Overall measures of wealth and income, including asset indices, have been predominately positively associated with ownership and use of clean cooking fuels57,68,69. The list of variables included in the economic status index can be found in Supplementary Note 3 and summarized in both survey waves in Supplementary Table 13.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 16}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We considered several sets of potential confounders of the relationship between implementation of a license law and perinatal outcomes based on a priori knowledge. First, we considered whether the composition of birthing people may vary across places and bias the observed association. Second, we considered whether economic and demographic characteristics of place may drive the implementation of a license law and impact perinatal outcomes. Third, we considered the overall state immigration climate as a potential confounder.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 17}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The scoring mechanisms for each policy domain were established by Grumbach (2018). First, 135 individual policies were classified as liberal or conservative. Liberal was defined as the use of state power to regulate the economy, redistribute income and wealth, protect vulnerable groups, or limit the government's ability to penalize irregular social behavior. Conservative was defined as the reverse. for each policy domain were calculated as the sum of the liberal policy scores minus the sum of the conservative policy ones. The summed scores for each domain were then standardized across states and years to give a 0 to 1 scale.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 18}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Fluvial and coastal inundation maps are available for the current and future climate following the RCP 4.5 and RCP 8.5. The SSP scenarios27-32 were used to represent the initial population numbers and to project population growth, income and economic growth for 2050. We applied the SSP 2 and SSP 5 scenarios as they matched well with RCP 4.5 and RCP 8.5, respectively. SSP 2 was a middle-of-the-road scenario, while SSP 5 was an energy-intensive and resource-intensive scenario. The former was used throughout the paper and the results of the SSP 5 scenario can be found in the Supplementary Information. See also Extended Data Fig. 1c.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 19}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The GCAM is an open-source global integrated assessment model (https://github.com/JGCRI/gcam-core/releases; for more information, see ref. 16 and online documentation http://jgcri.github.io/gcam-doc/toc.html). GCAM represents key interactions across the economic, energy, land and climate systems in 32 geopolitical regions in the world. It is a market equilibrium model that solves for the market prices and quantities of a large number of markets simultaneously. It is dynamic recursive with myopic foresight (that is, the model solution in each model period depends on the conditions in that period or periods before it). In this study, we use GCAM-USA v5.1, which is a version of GCAM with state-level detail in the United States26. Like GCAM, GCAM-USA is an open-source model. Detailed documentation for the GCAM-USA model is available online (http://jgcri.github.io/gcam-doc/gcam-usa.html). Here we summarize key model features that are relevant for this study. The model results for all main and supplementary scenarios are available from a public data repository51. GCAM-USA divides the energy and economic systems of the United States into 50 states and Washington DC, with state-level representation of socioeconomics, energy transformation (power generation and refining), carbon storage, renewable resources (wind and solar), electricity markets (with the representation of regional electricity grids) and consumer end-use energy demands (in buildings, transportation and industrial sectors).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 20}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Since labor is the only input in production, the labor used in producing goods in country n and sector j is a function of output: yj il (\u03c9j)=z j il (\u03c9j)l j l (\u03c9j), (2) where l j l (\u03c9j) is labor input and z j il (\u03c9j) is production efficiency. This suggests that the marginal cost of each good in country l is wl, the wage level in country n. The production generates carbon emissions ej il (\u03c9j) as a by-product. A firm allocates a portion \u03b6 j l of the output yj il (\u03c9j) to emission abatement activities to reduce its tax payment. On the basis of Copeland and Taylor (2001)31, we assumed the pollution abatement technology to be ej il (\u03c9j)=(1-\u03b6 j l ) 1 \u03b2 j l yj il (\u03c9j). The net production after abatement investment is, qj il (\u03c9j)=z j il (\u03c9j)[l j l (\u03c9j)](1-\u03b2j l ) ej il (\u03c9j)\u03b2j l , where z j il (\u03c9j)=[z j il (\u03c9j)]1-\u03b2j l and z j il (\u03c9j) are drawn independently across firms from a Fr\u00e9chet distribution with parameters \u03b8j: Pr(z j il <x) =exp(-Tj il x-\u03b8j). \u03b8j governs the dispersion of productivity for the affiliates located in different product locations. The firm's problem implies that the cost of unit input bundle is c j il =\u03b2j l -\u03b2 j l (1-\u03b2j l )-(1-\u03b2 j l ) (\u03c1l)\u03b2 j l (wl)(1-\u03b2 j l ) and \u03b2j l = \u03c1le j il c j il qj il , where wl is the wage and \u03c1l is the emission tax in country l. Following ref. 12, the average productivity is a combination of productivities in parent country and in host country, that is, we have Tj il =Tj i Tj l .\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 21}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We measured people's support for climate change solutions in both the pre- and post-survey using the following three items: (1) 'Addressing global warming/climate change should be a priority of the government' (strongly disagree\u2014strongly agree), (2) 'I feel personally responsible to help slow down global warming/climate change' (for example, by making changes to my lifestyle or paying higher taxes) (strongly disagree\u2014strongly agree) and (3) 'Some people say that climate change is real, but that the cost of fixing it today might not be worth the investment (that is, that the cost of fixing it today is higher than the cost of the damages caused by it)' (strongly disagree\u2014strongly agree). Responses were recorded on a seven-point scale. With a Cronbach's alpha of 0.84 in the pre- and 0.87 in the post-survey,  the internal consistency of our measure was found to be good.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 22}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We analyzed state-level annual observations for the temporal period 2006 to 2017 for the 50 U.S. states and the District of Columbia. The time period of this study corresponds to the first year in which the opioid prescription data were made available by the Centers for Disease Control (CDC 2019) and the last year of available mortality data.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 23}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To model these two different dependent variables, we present two sets of models, one for each outcome. First, for the number of vaccine distribution sites, we estimated a series of spatial error models. We calculated univariate global Moran's I statistics for our key independent variables that suggested that spatial autocorrelation was a problem and would therefore not meet the assumptions of ordineary least squares (OLS) regression. Furthermore, the LaGrange multiplier statistics indicated that the spatial error model was the most appropriate method to contend with this autocorrelation (Anselin, Florax, and Rey 2004). Specifically, we used a queen spatial weight matrix because this was found to best maximize global Moran's I for each of the key variables used in the models (Anselin 1995; Anselin, Florax, and Rey 2004). We also included Kelejian and Prucha (2010) robust standard errors to account for significant heteroscedasticity. However, of note, the term for lambda is not significant in the models presented in Table 2, suggesting that correlated errors in omitted variables may not be particularly a problem here. The OLS results were also virtually identical to what is presented here in terms of the sign, significance, and relative effect sizes for each of our variables. Because spatial autocorrelation was significant in our preliminary analyses, though, we chose to present the results as spatial error models. These results can be found in Table 2.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 24}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To estimate the amount of deficits in the power system, we simulated the difference between the expected, temperature-dependent electricity demand and the available generation capacity. We used a regression model to simulate the demand from observations of past load in the years 2012-2020. Available generation capacity was obtained from the expected available capacity according to reports, reduced by outages related to temperatures.According to ERCOT17, 67.5 GW of thermal capacity was available during the 2021 winter, but 4 GW of this may have been under maintenance. We therefore assumed a value of 63.5 GW of available thermal capacity before the freeze event.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 25}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The capacity spin up of LIMES-EU is fixed so that it matches the 2015 historical mix of installed generation capacities in EU ETS countries. Extended Data Fig. 5 illustrates that based on this standing capacity, the model-calculated dispatch then reasonable matches the historic power generation dispatch in EU ETS countries. The total modelled emissions from electricity generation in the year 2015 for EU ETS countries covered by LIMES-EU amount to 981 Mt CO2, closely aligning with the historical emissions of 967 Mt CO2reported by Mantsos et al.56 Because emissions from industry, heating and aviation are also calibrated to match their historical 2015 levels (as described in LIMES-EU documentation52), this calibration ensures that our model generates meaningful values for total emissions in the 2015 time step. Also, the model-endogenous investments in 2015 lead to standing capacities in 2020 that match historic wind and solar capacities in 2020. To this aim, we additionally assume subsidies for electricity generated from solar or wind sources (\u20ac0.04 kWh-1 for solar and \u20ac0.015 kWh-1 for wind) to represent the various renewable subsidies that were in place in most EU member states. Our model, however, underestimates the capacity additions of offshore wind until 2020, which took place mostly in the United Kingdom.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 26}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To assess the impact of energy audits on building EUI over time, we split the data into three time periods: pre-audit (average EUI in years 2011 and 2012), intervention (average EUI in years 2013 and 2014) and postaudit (average EUI in years 2015 and 2016). As a first step to test the significance of the audit effect, we used a two-way mixed design ANOVA in which the dependent variable is EUI, the within-group variable is time (with three levels as mentioned above) and the between-group variable is the intervention (with two levels, which indicate audited and non-audited buildings).One significant limitation of this approach is that it does not account for additional variables, besides time and intervention, that might be associated with changes in EUI, such as changes in occupancy characteristics.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 27}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    This paper uses data collected for a single year of project operation. Therefore, we provide a cross-sectional analysis that involves looking at the sector at a moment in time rather than assessing how it changes over time. It is particularly important to bear this in mind for the project performance characteristics presented in Table 4: because generation, revenue and operating costs may vary considerably from one year to the next, these data may not be representative of project performance in other years. Future research may wish to address these issues by collecting survey data on project performance over a number of years to construct a panel dataset.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 28}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To understand the empirical scope of health lifestyles, this study's design was different from typical health lifestyle approaches that focus on a specific set of physical health-related behaviors and their frequencies. We sought to collect qualitative data on children's health lifestyles, avoiding imposing preexisting notions around what constitutes health and health behaviors for parents, what children's health lifestyles consist of, and whether parents talk about health lifestyles. Recruitment materials said the study was about \u201cparents, kids, and well-being.\u201d Data collection strategies, procedures, and instruments were refined through pilot research. The data combined in-home family observations, parent interviews and focus groups, and key informant interviews in two neighboring middle-class communities in the U.S. West\u2014\u201cGreenville\u201d and \u201cSpringfield\u201d\u2014from September 2015 to May 2016. (All names and some potentially identifying details have been altered.) Our primary data source was 55 parent interviews: 35 with parents who also participated in a home observation (N = 30 families; in 5 families, both parents requested to be interviewed together) and 20 with parents who only participated in an interview. We conducted six focus groups (three for each community), including 21 parents (some of whom had also done interviews and/or observations). The nine key informants interacted with families in the local area (e.g., sports coaches, pediatricians, teachers). The 30 observation families (typically observed from the end of school to the start of the bedtime routine on one school night) included a fourth or fifth grader age 9 to 11. Parents in other interviews and focus groups had at least one elementary-age child. We chose these ages because family influences are still substantial but have been joined by peers, school, and child agency.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 29}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    In the investigation of recent lowpriced PV bids and PPAs, public announcements regarding, for example, financing terms, provide a window into some of the mechanisms by which these projects probably achieved their low prices. However, significant uncertainty remains, not the least of which surrounds the actual costs of these projects, for which there are conflicting reports21,33,34. Furthermore this 'top-down' look gives little insight into the relative impact of different cost-cutting mechanisms, and therefore provides little grounding for assessing whether these prices can be transferred to other markets; and as many of the details are proprietary, it would in fact not be feasible to attempt an exact reconstruction of any particular project. To circumvent this challenge, we adopted a bottom-up modelling approach, quantifying cost components based on a range of industry reports and analysis to build up a model of how these prices could be achieved under realistic global and local conditions.  This allows us to look at the relative impact of the many factors that contribute to the ultimate cost of producing electricity. Performance modelling was performed in System Advisor Model (SAM) for a plant designed to match the known specifications of Dubai's MBR solar park, phase 3, the first of the sub-3\u00a2 kWh-1 projects. The 'baseline' model scaled down the MBR model to 100MWac while retaining the same assumptions about hardware costs. LCOE was calculated in a spreadsheet (available on request) as: = +\u2211 \u2211 = + = + C LCOE i N O r i N E r 1 (1 ) 1 (1 ) i i i i using the annual energy yield calculated by SAM and discounting by the weighted average cost of capital. Performance modelling of the UAE plant (3\u00a2 kWh-1) uses International Weather for Energy Calculations weather data for Abu Dhabi; modelling for Sakaka (see Supplementary Note 1) used Photovoltaic Geographical Information System weather data (http://re.jrc.ec.europa.eu/pvgis/, retrieved June 2018) for Al Jouf airport (coordinates 23.694\u00b0 N, 40.088\u00b0 E, a few kilometres from the solar park site). The model was implemented in SAM 2014.1.14, based on the known or presumed specifications of Dubai's MBR phase 3, including large (310 Wp ) CS6X modules from Canadian Solar, 5000 W inverters from GE, an inverter loading ratio of 1.3 and single-axis tracking\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 30}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Most interviews were held in private offices at the clinic sites, and participants provided informed consent prior to interview initiation. Interviews lasted, on average, 71 minutes, with a range between 38 minutes and nearly 2 hours. The interview inquired about providers' history practicing medicine, their contraceptive prescribing patterns, and details about how they engage in dialogue with their patients about contraception. At the completion of the interviews, the providers received $40 grocery store gift cards.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 31}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    County-level waste availability data were obtained from the base-year estimates under the reference scenario in the US Department of Energy's BT16. BT16 estimates the biophysical potential, spatial distribution, economic constraints and environmental impacts associated with existing and potential biomass resources16. Waste resources included in this study comprise four types of waste: agricultural residues (14 feedstocks, including both primary and secondary agricultural residues as defined in BT16), animal manure (2 feedstocks), forest residues (4 feedstocks) and MSW (9 feedstocks, including food waste). Technical availability was defined as the maximum potential of waste resources without taking into account feedstock costs. BT16 reports dry weight of waste feedstocks, and wet weight was calculated with moisture content for a more precise estimation of energy consumption and emissions during the collection and transport stages.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 32}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The full survey instrument is available as part of the replication archive for this study. Our main outcome variables were based on two items, namely a climate agreement item and a climate cost path item. The climate agreement item was as follows: \u201cAs you probably know, many experts say that countries should take action to address global warming. NaTUrE ClmaTE CHaNGE Suppose [your country] is considering joining an international agreement to reduce greenhouse gas emissions. Implementing the agreement would mean that each household would have to pay on average [France, \u20ac28, \u20ac113; Germany, \u20ac39, \u20ac154; the United Kingdom, \u00a315, \u00a360; the United States, $107] more per month through, for example, higher energy prices. Generally speaking, do you approve or disapprove of [France, Germany, the United Kingdom, the United States] joining such an agreement?\u201d Respondents were asked to answer on a scale from 1 (strongly approve) to 10 (strongly disapprove). The climate cost path item was as follows: \u201cRegardless of your previous answer, suppose [France, Germany, the United Kingdom, the United States] is going to implement that international agreement and the household costs would still be [same costs as above] per month on average. However, there are different ways of distributing these costs over time.  The figures below indicate four alternatives. If you had to select one of the  options in a referendum, which would you chose? Please carefully consider the available options.\u201d The options were presented to respondents as shown in Fig. 1. The preferences for distributing climate costs over time, shown in Fig. 2, were calculated as the share of respondents who selected a particular time path. We investigated the role of different individual-level covariates using a multinomial probit regression. The four possible values of the outcome variable corresponded to the four time path options available to respondents. Our independent variables were the measures of consumption smoothing, patience and the sociodemographic covariates described above (the results are reported in Supplementary Table 2).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 33}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We establish a baseline scenario for the 2017-2060 period and 1,295 mitigation policy scenarios considering different intensities and portfolios of four major mitigation strategies (Supplementary Section 3).  The baseline scenario reflects future economic growth, energy consumption and carbon emissions under the current mitigation policies. The historical economic growth and energy consumption data for 2017-2021 are calibrated according to the NBSC28,30 and British Petroleum Statistical Review54. For 2022 to 2060, the projections of GDP growth, population, labour and industrial structure refer mainly to existing studies31,55,56. The energy consumption towards 2050 is calibrated by endogenizing energy efficiency improvement rates according to the projection of the IEA29 and extrapolated to the year 2060. In 2060, the annual GDP and population growth rate will decline to 2.5% and -0.6%, respectively; energy consumption will increase to 6,054 Mtce and carbon emissions will decrease to 7.9 GtCO2 .\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 34}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Race-ethnicity was divided into four groups: nonHispanic white, non-Hispanic black, Hispanic, and Asian. Less than 2% of the sample consisted of an \u201cother\u201d race-ethnicity group, and because of their small numbers, they were dropped from the analysis. The models also included controls for the sex of the respondent, marital status (married; widowed, divorced, or separated; never married), age (18-to 39, 40-64, 65-79, and 80 and over), education (less than high school, high school or equivalent, college or higher), insurance status, and poverty (below 100% of the federal poverty line for household income). All the models also controlled for the year of the survey using a series of dummy variables.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 35}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The MEPS survey includes the Kessler K6, a wellvalidated instrument assessing nonspecific psychological distress (Kessler et al. 2003). The K6 was not fielded in every round: In each calendar year, respondents in the first year of their panel were given the K6 in the second round of interviews, and respondents in the final year of their panel were given the K6 in the fourth round. The K6 asks about the frequency of six symptoms in the past 30 days. Respondents were asked: \u201chow often did you feel so sad that nothing could cheer you up; nervous; restless or fidgety; hopeless; that everything was an effort; and worthless,\u201d with response categories ranging from none of the time (0) to all of the time (4). The six items were combined to create a summary measure with scores ranging from 0 to 24. In addition to a continuous score, some models employed a categorical measure of significant distress, based on a threshold score of 13 or higher, as used in previous studies (Reeves et al. 2011).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 36}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    For experiment 1, we collected a sample of 894 Pennsylvanians that was demographically representative on age, gender, ethnicity and household income (based on 2019 American Community Survey 1-year estimates) and balanced on rural (25%), urban (25%) and suburban residence (50%) (see demographics in Supplementary Table 6). Our public sample was recruited by the survey firm Lucid. To recruit participants, Lucid partners with multiple double opt-in panels that invite participants through emails, push notifications and in-app pop-ups. Respondents are incentivized through partner suppliers in the form of cash, gift cards or loyalty reward points. All respondents from our public sample completed the survey between 7 February and 24 February 2022. Fifty-seven respondents who failed an attention check were removed from the sample and subsequent analyses (Supplementary Fig. 5). Mean response time was 16.9 min. Each respondent was asked to choose between five distinct pairs of randomly generated projects, testing support across a total of 8,940 projects. For both experiments, the attribute levels were fully randomized within and across project pairs, ensuring the non-parametric identification of causal effects of the attributes22,65. For this sample, probability weights were created with a post-stratification raking procedure using Census variables (from 2019 American Community Survey 1-year estimates). This procedure follows the methodology outlined in DeBell and Krosnick (2009) for the American National Elections Study66. Robustness tests including comparison across attention check failure and profile order are included in Supplementary Information.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 37}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The core of the modelling framework was developed for the conterminous US, including the entire USA coastline and all main river basins. It simulated flood risk at a yearly time step with representative household adaptation at a resolution of 30\u02ba x 30\u02ba and government adaptation at the county level. Homeowners could invest in DRR measures (elevation or flood-proofing of buildings) or take out/cancel insurance and governments could invest in elevating dikes. Both these adaptations and the proposed NFIP reform policies were captured in four policy scenarios. The model was run 50 times for each of these policy scenarios while also assuming different climate scenarios and socio-economic scenarios. The framework builds upon earlier versions of DYNAMO20,24. New components are the flood insurance market module, the addressing of coastal flood risk in addition to fluvial flood risk and the nationwide application of the model. For the method description of the  core model, please refer to ref. 20. See also Extended Data Fig. 1 and Supplementary Information.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 38}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We understand implementation as the process of translating public policies into operational and enforceable programs70. We primarily  investigate implementation through the process of rule-making. Through rule-making, city governments develop and issue specific regulations that establish rules and parameters by which to implement and enforce a policy71. In this way, rule-making is one of the first and most critical steps of the policy implementation process. Rule-making is also a critical site to analyse the operationalization of climate justice on the ground. Rule-making is where issues of politics and power most clearly intersect with policy implementation by providing an arena for city governments and other actors to contest and reinterpret the justice goals and mandates that were already embedded in climate policies during the policy planning process72.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 39}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We combined several datasets to determine the founding year of each cleantech company identified by the methods above.  The i3 dataset contains data on company founding year. USAspending.gov does not include information on the age of a business; DOE awardees and rejected ARPA-E applicants required manual research to determine founding year. When not available on the company's website, founding year was obtained from Orbis, Factset, public news sources and/or state business registration documents. We limit our dataset to companies that were startups in 2010, that is, with a founding year in the range 2005-2010.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 40}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our initial sample was composed of the 813 companies with approved SBTs as per the online SBTi database7 on July 20th, 2021. The SBTs in the SBTi database generally contain the following data of relevance to this study: sector, emission metric (absolute or intensity-based), emission scope (1, 2, 3 or a combination), base year, target year and targeted percentage reduction in the emission metric. We first excluded 28 energy generators and utilities (3% of the initial sample) due to our focus on companies that purchase energy. We excluded another 101 companies (12% of the initial sample) that only have intensity-based SBTs covering scope 2 to avoid the additional uncertainty associated with converting intensity targets to absolute emission targets. For companies with multiple SBTs covering different emissions scopes and target years, we selected a single SBT, prioritizing targets specifically for scope 2, when available (otherwise, we prioritized targets for scopes 1 and 2 combined over targets for scopes 1, 2 and 3 combined), followed by prioritization of the shortest target time span (that is, the difference between the base year and target year). In addition to the target data sourced from SBTi, we collected information on the scope 2 accounting approach that each SBT refers to (market- or location-based) from company disclosures to CDP (formerly the Carbon Disclosure Project)40 (this information is not provided by SBTi; see Supplementary Section 2.4 for more details). Note, however, that only around half of companies with approved SBTs reported to CDP. We were therefore left with 338 of the 813 companies after removing energy generators and utilities (28), intensity targets (101) and companies that did not report to CDP (346).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 41}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Climate change adaptation is defined by the IPCC as \u201cthe process of adjustment to actual or expected climate and its effects\u201d26. Adaptation of the agricultural sector to climate-induced changes in crop yields may include adjustments in consumption, production and international trade2. Demand-side adaptation is captured in GLOBIOM by changes in regional consumption levels in response to market prices. Supply-side adaptation includes the reallocation of land for each crop by a grid-cell and management system, and the expansion of cropland to other land covers23. Whereas Lecl\u00e8re et al.23 assess supply-side adaptation, here we focused on international market responses, in which our analysis approach is inspired by the 'adaptation illusion hypothesis' postulated by Lobell15 and confirmed by Moore et al.55. They argue that farm-level practices identified as adaptation measures by many crop modelling studies cannot be referred to as climate adaptation as they have the same yield impact in current climate as under climate change. In a similar manner, we intended to investigate whether, where and, if so, why trade integration has a larger positive impact on the risk of hunger under climate change. We defined the adaptation effect of trade as the sum of the effect of reducing trade costs on hunger under current climate (direct trade effect), and any additional positive or negative impact of trade integration under climate change (climate-induced trade effect). The adaptation effect of trade can be understood through Ricardo's theory of comparative advantage (Supplementary Text)11,12. Reducing trade costs promotes trade according to comparative advantage56 and facilitates the role of trade as a transmission belt in linking food-deficit and food-surplus regions57. Climate change impacts differ across crops and regions8. Depending on the spatial distribution of these impacts, the current pattern of comparative advantage may be intensified, maintained or substantially altered. This may lead to increased food deficits in certain regions. Trade is argued to have a larger role under climate change as it facilitates adjustment to changes in comparative advantage11,12 and enables food surplus to be linked with food deficit regions6,7,57.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 42}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Party identification was measured with the twostep approach used in the Socio-Economic Panel, which has been conducted since 1984 by the German Institute for Economic Research61. In a first step, respondents were asked whether they hold a preference for a specific party. If they replied in the affirmative (which was the case for 1,275 respondents, or 64% of the main sample), they were then asked which of the seven parties represented in the lower house of the German parliament they identify with, or whether they preferred another party. To measure perceived scientific consensus, respondents were asked to indicate the percentage of climate scientists worldwide who think that the increased concentration of carbon dioxide in the atmosphere since the middle of the 20th century is primarily due to human activity. They used a slider to choose a percentage between 0 and 100%. Strong ties with the coal industry were measured by asking whether respondents themselves or someone they know works in a coal mine or a coal-fired power station or has done so in the past.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 43}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We adjusted for controls, both time varying and invariant, that may confound the association between unionization and health. Demographic controls included age, year of birth, sex, race (White, Black, other), and four-category census region of residence (Northeast, South, Midwest, West). We included two measures of marital status: total years married and whether the respondent is married in a particular wave. We included an indicator of whether a respondent had a college degree by the age of 40.4 We included three health-related measures: the respondent's retrospective self-assessment of general health at ages 0 to 16,5 smoking status at ages 60 to 79, and the proportion of observed waves that a respondent had health insurance from 1999 onward, the first year health insurance information is consistently available. We included eight measures of contemporary and career employment. First, we included measures of a respondent's employment status at ages 60+: working, retired, unemployed, or not in the labor force. Second, we included the respondent's ages 60+ posttax and transfer total household income, divided by the square root of the number of household members. Third, we constructed 19 industry categories following Western and Rosenfeld (2011) and assigned respondents the modal category we observe at ages 18 to 60. Appendix materials in the online version of the article include replication with percentage waves in industry categories. Fourth, we constructed 12 large occupation categories and assigned the modal observed category from ages 18 to 60. Fifth, we assigned the respondent's modal region of residence from ages 18 to 60. Sixth, we included a measure of total years employed between ages 18 and 60 (percentage employed yielded the same results). Seventh, we included the percentage of years that a respondent was self-employed. Eighth, we combined information from occupation and industry, harmonized to 1990 Census Bureau classification schemes. We made all possible combinations of the 200 industry categories and 275 occupation categories observed in the PSID and counted the number of unique combinations each respondent held between ages 18 and 60. We used this measure to proxy labor market position changes. Appendix materials in the online version of the article include results with and without these career controls.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 44}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The research comprised two modeling experiments to address two research questions. First, we evaluated two scenarios of the spatial distribution of rainfall in causing flooding within the Warren area. For this purpose, STORM2014 precipitation data were configured as a grid with a resolution of 500 m x 500 m using rainfall data obtained from the Detroit City Airport rain gauge. This gridded product was used as model input in the first scenario, 'HR-Integrated' (results are presented in Fig. 2d). The drainage system was designed to closely resemble realworld conditions, allowing for water exchange between the inside and outside of the Warren drainage system based on the dynamically changing distribution of hydraulic head over the surface and below ground in storm sewers. In the second scenario, the gridded rainfall data for the Warren area were set to 0 mm for the duration of the STORM2014 event (that is, 24 h). This scenario was named 'NR-Integrated' (Fig. 2e). In the second experiment, we explored the functioning of two stormwater sewer outfalls (Fig. 2b,c) using three different model configurations. The first set-up represents the most realistic design  by allowing backwater to occur (water from the open channel flows back into the sewer system through the outfall) (termed 'Integrated' outfalls). The second set-up assumes the current sewer system is  unaffected by water levels at the outfall locations, maximizing drainage  capacity by allowing unrestricted discharge from the stormwater  system into the open channel without backflow from Bear Creek (termed 'Controlled' outfalls). The third set-up precludes any water exchange at the outfalls between the stormwater system and open channel, with the total outflow from the system stored in an underground storage  sized to contain all runoff from the Red Run watershed under  the STORM2014 event (a volume of ~24.77 million m3) rather than entering the open channel. We term this case 'Water loss', the results of which are shown in Supplementary Fig. 3.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 45}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To explore the optimal utilization of waste biomass resources, we developed three alternative scenarios: MEP, MNE and MER. For all scenarios, the optimal conversion pathway for each feedstock was selected on the basis of the maximum value of energy or emission reduction. Under each scenario, the countylevel results were then added up to obtain the potentials for total renewable energy production, net energy and emission reduction at the national level.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 46}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We had access to historical electricity consumption data from July 2015 to December 2019 for all the customers. These data were provided by the utility, after being verified by the electricity distributor, and constituted our main outcome variable. Similarly to other works, we computed the average daily electricity usage in a month from the total monthly consumption and normalized it by dividing by the average post-period control group consumption and then multiplying by 100 (ref. 17). We also computed the average daily pretreatment electricity usage as the mean of the average daily consumption in a month between July 2015 and June 2016.We also had access to information on the treated customers' engagement with the reports and on the reports' contents. These data were provided by Opower. We knew when a eHER was sent and when a customer opened or clicked on a report, although we did not know which one. By opening the reports, customers were able to view the neighbour comparison; by clicking on it, customers were directed to their personal page on the utility's website, where further information, such as energy saving tips and bills, was available. On average, 64 and 30% of the customers opened and clicked on an eHER, respectively, at least once over the two years after the programme launch. As for the eHER augmented with the normative prime, 55 and 9.7% of customers opened and clicked at least once in the two months after its receipt, respectively.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 47}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The experiment was implemented in September 2018. Participants included the entire population of California LMI homeowners who had adopted solar with the non-profit GRID Alternatives, had interconnected their solar system between 2004 and 1 June 2018, and for whom GRID had a valid mailing address, N = 7,680. The vast majority of these customers qualified for California's Single-family Affordable Solar Homes (SASH) programme, of which GRID Alternatives is the programme administrator. SASH provides incentives at US$3.00 W-1 to homeowners with household incomes below 80% of the area median income (AMI), who live in a home defined as affordable housing by California Public Utilities Code 2852, and who receive electrical service from Pacific Gas & Electric, Southern California Edison or San Diego Gas & Electric. Applicant roofs are also screened for solar suitability, and solar installations must meet a minimum performance requirement. For our study population, 32% of the population had a household income below 30% AMI, 27.4% were between 30% and 50% AMI, 38.5% were between 50% and 80% AMI, and 2.1% were missing income data. Where SASH incentives are insufficient to cover the entire cost of a PV system and installation, GRID sources supplementary funding to provide the PV system at no cost.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 48}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We implemented a standard two-stage analytic framework, to estimate the association between short-term exposure to daily wildfire-specific PM2.5 and cause-specific respiratory hospitalization. The two-stage design is a flexible and computationally efficient analytical framework commonly used in environmental epidemiology to model large, heterogeneous data from multiple communities19,47-49. This approach allows for separate modelling of community-specific characteristics, preserving crucial local nuances and mitigating potential biases that could arise from pooling diverse data into a single model (Supplementary Methods 3).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 49}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used data from the U.S. restricted use natality files, 2008 to 2021 (National Vital Statistics System 2021) and linked these data to county- and state-level characteristics using the resident county and year. We started the analysis in 2008 because this is the year when Secure Communities was launched and funding for 287(g) dramatically expanded\u2014two programs that involve local law enforcement in immigration enforcement and have been critical to the rise in deportations following a traffic stop (Moinester 2019). These programs contribute to immigrants' fears of driving without a license and, in turn, may be consequential for perinatal health (Rhodes et al. 2015). The target population for this study was Mexican and Central American birthing people who were likely to be impacted by the passage of a license law. We believe that undocumented birthing people would be most strongly impacted because they would personally receive an additional privilege and reduction in deportation risk because of the implementation of this law. The impact of these laws may also spill over to birthing people who are not themselves undocumented but whose partner or other loved ones are. These persons may experience a reduction in stress because of the passage of the laws or increase in financial resources due to changes for others in their household. Legal status is not included in birth certificate data. However, to make the study population more likely to be undocumented or have undocumented partners or loved ones, we restricted the analysis to birthing people born in Central America or Mexico. These regions account for 67% of the U.S. undocumented population (Migration Policy Institute 2019). As a sensitivity analysis, we stratified by maternal education to determine whether associations are stronger among individuals without a high school education, who are more likely to be undocumented (Passel and Cohn 2019).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 50}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To develop the drivers of changes in financing conditions, we apply an interview case study design with two stages of data collection53. First, open exploratory interviews (N =  8) were conducted to gain early insights on the dynamics and drivers of changes in financing conditions and to define the structure for the second phase of the interviews. Second, we conducted 33 semistructured interviews with employees from debt and equity investment firms who had significant experience in the renewable energy finance industry (23 of these interviewees are the same individuals who provided the quantitative data mentioned above). Note that we contacted three investment professionals from the exploratory interviews again for the semi-structured interviews and the collection of project financing conditions data. If more than one researcher conducted an interview (N =  15), one of them summarized it using the recording, transcript and notes. If only one researcher conducted the interview (N =  26), the resulting summary was cross-checked by another researcher. This procedure ensures accurate and consistent recording, expands the scope of insights and enhances confidence in the findings53. Following Eisenhardt's approach53, we continued holding interviews until no additional insights were observed.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 51}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    I utilized data from the Survey of Health, Ageing, and Retirement in Europe (SHARE), a panel survey representative of individuals ages 50 and older across various European countries. SHARE covers many topics, including economic, demographic, health, and family matters (Schr\u00f6der 2011). Specifically, I focused on the SHARELIFE data collected during the third and seventh waves of SHARE, which provides detailed life histories, including employment and family formation experiences from childhood to advanced age, for women born between 1924 and 1965. More details on the data source are provided in Appendix A in the online version of the article.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 52}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To estimate the health and labour consequences of supply-side policies, we build an empirically validated model of oil production to estimate field-level oil production and GHG emissions pathways under varying policy scenarios. These estimates drive our projections of pollution dispersion, mortality effects and local employment, which are used to quantify health and labour impacts under different policy and GHG emissions-target scenarios. We further examine the equity impacts of these scenarios focusing on how health and labour impacts are distributed between disadvantaged and other communities. Throughout, we use nominal prices in both the estimation and projection parts of the analysis. When presenting health and labour impacts, we calculate net present discounted values in 2019 US dollars after applying a discount rate of 3% and an inflation rate of 2%.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 53}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    On the basis of the different initial hypotheses, we collected a broad set of possible explanatory variables at the country level. To capture stranded asset risks, we used both a measure of the size of a financial sector and the approximate carbon exposure of the country's GDP. First, we used the World Bank DataBank's domestic credit provided to the private sector measure, as a share of GDP, from the most recent full coverage year in 2019 as a proxy for financial sector size53. This measure is a commonly used proxy for financial depth, which captures the financial sector's size relative to the domestic economy54. We also calculated the economic value contributing to a country's GDP from the oil and gas sector for the year 2021, using the Global Resource Input-Output Assessment model, a multiregional input-output database that captures input and intermediate goods trade across the world55. This dataset includes not just economic value produced and traded, but also value added by each economy into the value of final goods. This measure best captures the economic value the oil and gas sector contributes to an economy. For data on the growth of the renewable energy sector across countries, we used yearly data from the International Energy Agency on renewable energy's percentage share of primary energy supply and calculated the growth rate from 2018 to 202156. We used the 2022 exposure component of the ND-Gain country index to capture a country's physical risk of climate change impacts57. To measure climate policy stringency, we used the OECD's Climate Policy Stringency of adopted policies index for the most recent year available, 202058. To capture public sentiment about climate change, we used data from the YPCCC's survey, conducted in 2022, that produced population breakdowns of sentiment on climate change, by percentage59. We grouped the alarmed and concerned audiences together to capture the share of the population concerned about climate change. This survey is the most comprehensive cross-country sampling of public sentiment about climate change so far, but it still is missing a handful of countries from our dataset, most notably China and Russia. We substitute in a data point for China from a comparable 2022 survey from the International Monetary Fund, which includes the share of the population that feels that climate change will affect them or their family now up through the next 10 years60. We discuss this process more in Supplementary Note 6.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 54}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    For each set of models, we first present a model with only the clustering scores and ZIP-code-level control variables included (Model 1). Then, we add the health care resource variables one by one in the model (Models 2-5) to avoid the problems of multicollinearity and to isolate the effect of each organizational type as health care organizations tend to agglomerate. To our knowledge, no formal mediation test exists that can account for the spatial dependencies in the models and the multilevel structure of the second set of models. Therefore, we used an informal approach and examine change in the effect sizes with the inclusion of certain variables.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 55}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To isolate the relative effects of household demographics on adoption choices we use the following logit model:p(CS) = alpha+D\u03b2+S+\u03b5(1)Where p(CS) is the probability that a household is a community solar adopter (as opposed to a rooftop adopter), D is a vector of dummy variables for the four demographic dimensions and S is a state random effect. We convert the income variable into a dummy value by bifurcating the records into households that earn more or less than the state median income. The coefficient of interest is \u03b2, which represents the statistical association between household demographics and the household's adoption choice. Note that the model is not designed for causal inference. Household adoption choices are probably driven by numerous idiosyncratic factors that could correlate with the demographic factors. The purpose of this model is to compare the relative weights of the \u03b2 coefficients to understand which demographic dimensions are most strongly associated with household adoption choices. We use state random effects to account for the possibility that community solar has distinct impacts on adopter demographics in different states with distinct policy contexts. In addition to comparing the coefficients, we also implement variations of the model in equation (1) with different combinations of the demographic factors. We then compare Akaike Information Criterion (AIC) values across those models (Supplementary Table 6). The AIC is a metric that simultaneously measures prediction accuracy while penalizing models with more variables. The AIC comparisons provide another way of comparing the relative contributions of demographic differences to household adoption choices.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 56}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The resulting sample of providers was heterogeneous. Through snowball sampling, I was able to home in on actors who were known within their institutions to have knowledge and experience working with substance-using patients (e.g., clinicians with a special interest in perinatal substance use or perinatal social workers who were often responsible for making hotline calls to child welfare and communicating with patients after they have been tested). None of the hospitals in this sample had instituted formal universal screening protocol, and all of the providers in this sample discussed drug testing as a discretionary process. These findings are not intended to generalize to any one group  of professionals or setting. The benefit of a diverse sample is that it provides various professional vantage points at different points of care to reveal the effect of hybridity on decision-making processes that may be transferable to the study of other professional groups, institutions, or social problems spanning medical and legal institutions. I conducted semistructured interviews in person and over the phone (eight individuals were unable to meet in person) that lasted on average 45 minutes to an hour, with the longest interview spanning over 3 hours. The interview schedule centered around the provision of care for substance-using patients, including questions regarding how substance use was determined, drug screening and testing practices, hospital procedures and treatment protocol, professionals' attitudes toward substance-using patients, medical interventions for maternal substance use, and child welfare involvement.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 57}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The case selection includes three dimensions: technology, country and project type. First, we focus on solar PV and wind onshore technologies, the most deployed non-hydro RETs. In 2016, solar PV and wind onshore technologies accounted for a global capacity of 291 GW and 452 GW, respectively (for example, compared with 14 GW for wind offshore generation)46. Second, we focus on Germany, one of the earliest markets to adopt these technologies. Germany added the most solar PV capacity in 13 of the 17 years analysed, and the most wind onshore capacity in 8 of the 17 years analysed46. Our sample period begins in 2000, when Germany enacted its landmark legislation on renewable energy sources (EEG), with a feed-in tariff that triggered large-scale renewable energy investments23. The feed-in tariff was never changed retroactively. The German electricity market has been liberalized since 199823, and the vast majority of investment in RET was private47. Third, we restrict the analysis to project finance structures, exploiting the fact that 96% of large solar PV projects and 88% of large wind onshore projects in Germany between 2000 and 2015 were undertaken using project finance24\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 58}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    All the samples from the different countries were pooled when testing H1, H2 and H3. With 1,400 respondents in four countries and 1,000 respondents in one country, the total sample contained 6,600 respondents. These were then divided into seven groups (1,000 respondents in each group). To test H1, H2 and H3, we used independent-sample one-sided t tests and ordinary least-squares regression models with robust standard errors (results reported in Supplementary Information). We used the standard P < .05 criterion for determining whether there are differences between the groups. Hypotheses H1, H2 and H3 were supported if the null was rejected, and the estimates are statistically significant and have the expected signs and directions for both these tests. To test H3, group 3 was compared with an aggregated group based on group 4, group 5, group 6 and group 7. For the exploratory part where we investigated the role of individual factors for policy support, we used ordinary least-squares models.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 59}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We replicate demand and fuel prices variability as follows. The initial data include 21 annual demand data series and four annual series for fossil fuel prices (natural gas, coal, oil and uranium). All of them are for the period between 1990 and 2021. We detrend each of these series (after taking logs) using a Hodrick-Prescott filter42 with lambda set to 100, following the standard approach for annual frequency data. This procedure results in 25 residual series: each of them can be interpreted as the (percentual) deviation from the respective series trend. By construction, these residuals have zero or close to zero average. We compute the variance and covariance matrix of these series: the components of this matrix capture the covariance between each of the 21 country/areas and the covariance of each of them with each of the four fossil fuel prices. Elements along the diagonal capture the variances of each of the 25 series.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 60}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    In the second step of the analysis, we use our empirical estimates to calculate the expected reductions in CO2 emissions that can be causally attributed to policy diffusion. For this purpose, we use the estimated coefficients of all control variables and the spatial lag and feed them into Monte Carlo simulations of policy adoption and policy diffusion using the model in equation (1). We construct counterfactual scenarios that allow us to quantify the emission reductions that can be attributed to diffusion. For every country i, we compare a scenario A in which country i adopts carbon pricing in year t with a scenario B in which country i does not do so. For each of the two scenarios, we calculate the hazard rate of policy adoption at time t + 1 for all other countries j = i based on equation (1). The difference between the hazard rates of the two scenarios A and B can then be considered the additional hazard of policy adoption in country j that can be attributed to policy diffusion from country i.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 61}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We collected available auxiliary data from each source to either harmonize the data or integrate those parameters as control variables in the regression analysis to compare and validate the results: (1) value type, differentiating between cost or price, with the latter typically including additional overheads, mark-ups, indirect costs or supplier profits. However, we denote that both terms are also used synonymously.  (2) Application type, differentiating between automotive- or HDV-certified values, as altered requirements and scales also lead to different configurations, designs and costs. (3) Currency and (4) reference year information were collected to ensure accurate contextualization and temporal accuracy. (5) Scenario information was collected, differentiating between low (mass-market), high (niche market) and medium. (6) Forecast method, differentiating between literature-based projections, expert elicitation, detailed bottom-up cost modelling or learning and experience curves. (7) Data originality, differentiating between original or adopted values. (8) Integration level, differentiating between cell- or system-level values for batteries and stack- or system-level values for fuel cells. This raw data are available  for download, yet proprietary is anonymized.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 62}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We collected 819 sediment samples from 58 coastal wetlands, including unvegetated (tidal flats, N = 19) and vegetated (seagrass meadows, N = 10; tidal marshes, N = 14; mangrove forests, N = 15) coastal ecosystems along Chinese coastlines from the cold temperate zone (~40\u00b0 N) to the tropical zone (~19\u00b0 N) (Fig. 1a) during 2010 to 2022. We measured sediment Hg concentrations using a direct Hg analyser (DMA-80, Milestone), following the US Environmental Protection Agency Method 7473 (ref. 9). The limit of detection of the Hg analyser was 0.1 ng g-1. The performance of the Hg analyser was evaluated by multiple measurements of certified reference materials GBW07314 (marine sediment) and GBW07405 (soil). Results were not statistically different from the certified values, with Hg concentrations of 47.1 \u00b1 3.9 ng g-1 (1sigma, N = 57, certified value of 48 \u00b1 12 ng g-1) for GBW07314 and 282.9 \u00b1 12.5 ng g-1 (1sigma, N = 16, certified value of 290 \u00b1 40 ng g-1) for GBW07405. We measured LOI as the loss of weight of a sediment sample ignited at 550 \u00b0C for 8 h by a Muffle furnace9.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 63}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To build work-family life histories, participants were prompted to recall significant milestones, such as job-related changes and key family events, annually. These included moving out of their parent's home, cohabiting, marriage, childbirth, widowhood, and divorce. Leveraging these data, I crafted a life history data set in which each individual is observed annually from age 15 up to their age at the time of the survey. Their recorded state remained unchanged until they indicated a change in status. This information was used as an input for sequence analysis to construct work-family life histories, as detailed in the empirical strategy section. For more information on the measurement of work-family statuses throughout the life course, see Appendix B in the online version of the article.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 64}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The first stage in identifying variables to use as the bases for the cluster analysis was the development of measures of preference for the five business archetypes. Five measures were derived from the various questions on the survey. (1) Likelihood to adopt each archetype, using a single question asked after each archetype, was scored on a number of sematic differential attribute scales. (2) Adoption spread was the highest value of likely minus the lowest for each individual to generate a signal of preference certainty. If a person scored one or more options very highly in terms of likelihood to adopt, and another option very low, they would have a larger spread than someone who scored all options similarly. (3) Probability of adoption was the number of times chosen during the paired comparison experiments divided by the number of times available to be chosen. (4) Weighted probability of adoption was calculated by multiplying the probability of adoption score by the likelihood score. (5) Preference stability was a test of internal consistency calculated by using an excel macro to detect reversals between each combination of three options and then adding up the number per person. The majority of people were perfectly internally consistent (that is, 76% did not reverse their ranking of options across the three possible combination with each option).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 65}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our policy-specific dataset includes 168 observations across the 47 countries and identifies the country; the year of the policy (91% of the policy observations are between 2019 and 2023); the name of the policy; the policy description; the data source (webpage link); whether the policy includes a requirement of other actors (for example, a regulatory rule for banks to comply with, or a request for information) or only pertains to the central bank operations (for example, information published by the bank or a change in how the bank manages its funds); whether the policy aims to re-risk, de-risk or both; the policy function class (information, economic or structural); and the relative 'cost' of the policy to the central bank (the relative degree to which the action is costly to the central bank to enact, as interpreted by what is going to have a material impact on the financial system and what might have a resource cost) (see Supplementary Note 5 for an expanded discussion of this cost concept). To review some examples of these specific policies and the policy classification systems, please see Table 1 and Extended Data Table 1.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 66}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used microdata from a large set of nationally representative household surveys of different countries to estimate energy and cooking technology choices for regions of the world. We aggregated nations in line with the 11 regions of the MESSAGEix-GLOBIOM model42. The datasets used to represent each of these regions are presented in Supplementary Table 1, with a focus on regions of the world where access to clean cooking is lacking. Regions where access is not an issue (that is, North America (NAM), Western Europe (WEU) and Pacific OECD (PAO)) were included in our analysis and modelled independently, but are presented clubbed together in a single other or rest of the world region in some results.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 67}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Data harmonization, based on the upper parameters, ensured that all data points were specified as system-level OEM purchase prices in \u20ac2020for the respective component. Initially, this involved (3) currency conversions based on the respective historical exchange rate (subject to the reference year or release date) and (4) inflation adjustment to 2020 levels (annual mean over all member states of the European Union (EU-27) issued by the European Commission and downloadable via Eurostat). Potential inhomogeneities caused by (1) cost or price type, (2) application type or (8) integration level are harmonized based on studies that explicitly state multiple values differentiated according to (1), (2), (8). Hence, all cost values were topped with a 35% surcharge (median value from battery data as no temporal trend could be identified) to derive OEM purchase prices. Scaling automotive-certified components to HDV-certified ones, data showed a temporal trend for batteries but not for fuel cells. Hence, we used a decreasing scaling factor for batteries from around 80% in 2020 to 50% in 2030 and 20% in 2050, indicating higher integration, potential enhancements through on-purpose designs and usable synergies. For fuel cells, all automotive-type values were topped with a 100% surcharge (median value). For cell-to-system or stack-to-system scaling, data showed a clear temporal trend for both batteries and fuel cells. Therefore, we used a decreasing scaling for batteries from around 40% in 2020 to 30% in 2030 and 20% in 2050. In contrast, we used an increasing scaling factor for fuel cells from 60% in 2020 to 90% in 2030 and 125% in 2050, meaning that the cost share of the actual stacks on total system costs was expected to decrease. Supplementary Figs. 2-4 provide more details. These harmonized data are available for download.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 68}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We build a multicountry multi-industry general equilibrium model by incorporating MNEs, international trade flows and corporate tax to quantify the emission effect of corporate tax changes27. Specifically, we extended the quantitative trade and MP model developed by refs. 11,12, by incorporating corporate tax and linking production to environmental emissions. In the model, a firm from country i can serve country n by building an affiliate (MP) in country l and shipping goods to country n (Trade). This entails MP costs associated with the pair {i, l} and trade costs associated with the pair {l, n}. Given these costs between countries, a firm in any country chooses how much of its products will serve market n, and via which production location it will serve market n to maximize profit. Then, a corporate tax cut in country B would increase the profits of the production located in B and attract more MP activities and stimulate more trade flows from B. The expansion of production in B would directly increase the CO2 emissions through a scale effect. It would also increase labor demand and lift the wage level in B, as labor is a necessary input in production. However, the wage change in B would further reshape MP flows to B and trade flows from B by influencing marginal production costs. Meanwhile, tax cuts in B would impact output and emissions in B and other countries. For example, the tax cut in B will decrease the income of its competitors by taking up their market share. In other words, corporate tax cuts in one country would impact both MP and trade flows across countries and reshape global production and emission networks.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 69}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our main dependent variable is annual deforestation9 extracted at the grid-cell level for 2011 through 2018. We use this annual measure of deforestation (rather than the sum of alerts for that year) because the alerts are reliant on single observations (making them more susceptible to error) and are designed to be conservative, whereas the annual product maps loss are based on the entire year and can capture the area of loss more accurately9. We prefer a binary measure of deforestation that is equal to one if there is a positive amount of deforestation during a given year. The reason for this is that the two continuous outcomes (per cent deforested and a winsorized version of per cent deforested) have substantial outliers, even in the case of the winsorized measure. For example, the per cent deforestation outcome ranges from zero to 100. However, the measure at the 75th percentile is zero, and at the 95th, 3.57. For the winsorized version of this variable, the 75th percentile value is still zero, and the 95th is 3.29. This type of skewness, particularly when combined with measurement error, can result in considerable bias in regressions.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 70}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Most research on fossil fuel subsidies is concerned with estimating the damages they cause and the benefits of subsidy reform1,2,36. Our study builds on two smaller bodies of positive research. The first is made up of cross-national quantitative studies of gasoline taxes and subsidies\u2014the most readily measured type of fossil fuel subsidy. In general, these studies demonstrate that gasoline taxes and subsidies are closely associated with slowly changing economic factors, especially income per capita and fossil fuel wealth. The role of politics is more uncertain: some studies find a link between fuel taxes and political institutions29,37,38, whereas others do not39.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 71}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    In conjunction with the capacity investment decisions made in the first stage, investors can sign contracts with consumers that settle based on the energy price in the second stage. Assume a small set of contracts \u03b7k frs I is available to trade. Let \u03bbfrst be the price of energy in time block t given fuel price f, profile r and demand shifter s, that is, the dual variable that corresponds to the power balance constraint in equation (2) divided by the length Lt , and let \u03b7k frs I represent the payout  of contract k2K I given this scenario. A call option gives the purchaser the right to buy a unit of energy for a predetermined price if the spot price exceeds that level. Thus, if contract k indexes a call option that covers all the time blocks with strike price \u03bbk, we can calculate: \u03b7k frs\u00bc X t2T Ltmaxf0;\u03bbfrst\ufffd\u03bbkg \u00f06\u00de If k instead indexes a futures contract that covers all time blocks at price \u03bbk, the payout is calculated as: \u03b7k frs\u00bc X t2T Lt\u00f0\u03bbfrst\ufffd\u03bbk\u00de \u00f07\u00de We also define a unit contingent contract that tracks the availability of generator g, a construct often used for variable technologies. When k indexes a unit contingent contract for generator g, the payout is calculated as: \u03b7k frs\u00bc X t2T AgrtLt\u00f0\u03bbfrst\ufffd\u03bbk\u00de \u00f08\u00de\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 72}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We limited our time horizon to the period between 2012 and 2019. First, we excluded the years before 2001 because of discontinued regulations that may have distorted repowering decisions from today's perspective. Second, we also excluded the years from 2001 to 2011 as, during that period, the Danish government provided policy incentive programmes for repowering (Supplementary Note 1) that could have confounded our analysis. Third, we excluded projects that involved research and test turbines, as these turbines are subject to different regulations. Of the 102 identified wind projects, 8 were experimental test projects, that is, turbines established and dismantled at test sites. In total, 70 test turbines were dismantled during the investigated period. Fourth, we excluded household wind turbines, that is, turbines with a generation capacity of 25 kW or less, as there are different regulations for these types of turbines. During the investigated period, 77 household turbines were dismantled. Fifth, we excluded a dismantling project that was part of an infrastructure development project, in which 26 turbines were dismantled because of the construction of the Femern tunnel in Southern Denmark. Overall, we determined that 221 out of the relevant 601 dismantled turbines were repowering related.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 73}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We assembled several indicators of community socio-economic status and demographic composition at the ZIPcode level from the US American Community Survey (ACS)55. These are variables potentially associated with coal-fired power plant exposure that might also predict asthma exacerbations56 and included total population, number of non-Hispanic black individuals, number of individuals without health insurance coverage, number of individuals 16 years and older that were unemployed, number of individuals 25 years and older without a high school diploma or equivalent and number of individuals with income in the previous 12 months below the federal poverty level. To create a time-varying dataset, we linked multiple 5-yr surveys because annual ZCTA-level estimates were not available. For example, we used the 2008-2012 ACS to estimate ZCTA characteristics in 2012 and the 2009-2013 ACS for 2013, which we then assigned to ZIP codes using a crosswalk. Finally, we downloaded ZIP-code-level meteorological data on ambient temperature, relative humidity, windspeed and atmospheric pressure from the USEPA57\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 74}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We use econometric models to identify policy diffusion in the data on past policy adoption. To do so, we estimate a model that relates adoption of a policy in a country i at time t to the adoption of the same policy in other countries j = 1, \u2026, Nc , j ! = i prior to time t (with Nc being the number of countries in the sample). This is a common  empirical strategy to identify policy diffusion and has been used in the literature on climate policy7,20,21,41. Technically, the model accounts for the mutual influences between countries with spatial lags, which  are calculated as a weighted average of prior policy adoption in all  other countries. We use alternative weighting schemes based on geographical proximity, trade and international institutional linkages, which we consider as representing some of the alternative diffusion mechanisms cited in the main text. The choice of our model is informed by two characteristics of our dependent variable. The first characteristic is that any possible future policy adoption is unobserved, which means that our dependent variable is right-censored. Specifically, at the time of analysis, policy adoption is only recorded in the Carbon Pricing Dashboard of the World Bank up until April 2022, which means that 2021 is the most recent year in our sample. The second characteristic is that our dependent variable is binary, taking on only values 0 or 1. Both these characteristics are common in survival analysis, which is also referred to as event history analysis, and can be addressed with proportional hazard models.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 75}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The Louisville Metro Department of Public Health and Wellness provided quarterly combined counts of asthma-related hospitalizations and ERVs among all ages for the years 20122016 for all Louisville ZIP codes, which we restricted to the 35 ZIP codes with population greater than 5 in 2012. Hospitalizations and ERVs were considered asthma related if the following International Classification of Diseases 9 or 10 diagnosis codes were present in the first through to the third diagnosis positions: 493.XX or J45.X. To present health data spatially, we used a crosswalk to map ZIP codes to ZCTAs.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 76}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Conjoint experiments allow researchers to compare trade-offs across multiple dimensions by randomly generating bundles of attributes and asking respondents to pick between two such choice bundles. This design more closely captures decision-making in realistic contexts than asking respondents to independently evaluate options. Use of conjoint experiments to measure public preferences has increased in recent years across the social sciences59-61. Conjoint experiments have high external validity and lower social desirability bias compared with other methods of eliciting preferences62-64. In experiment 1, we examine 24 project dimensions in a demographically representative sample of PA residents. In experiment 2, we examine a reduced set of 19 dimensions in a smaller sample of local elected officials. We use a limited number of attributes and increase the number of choice pairs that respondents evaluate, to ensure that we are powered to detect 0.07 and 0.05 effect sizes despite the smaller sample size. We selected attributes to drop on the basis of the results of experiment 1 (for example, eliminating attribute levels that did not have statistically significant variation, like in project benefits, and adding an additional attribute level in response to feedback from researchers experienced with elite samples). We asked respondents to choose between two energy infrastructure projects in their area that varied on five dimensions. The full list of attributes is displayed in Supplementary Table 5. In experiment 2, we additionally asked local elected officials to report their perceptions of constituent support for each proposed pair of projects.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 77}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The raw dataset was filtered to obtain a dataset that only includes startups of interest to this analysis using the following steps and building on the approach in Surana et al.9. First, startups that did not have a clear connection to climate were identified and excluded from the dataset. This was done using keyword terms in the description, such as startups focused on ride sharing for which the climate benefit is unclear. Supplementary Table 17 provides all filtering terms. Competitors of these excluded ventures, as identified by i3, were also excluded. In addition, startups that i3 categorized in the 'other clean tech' sector were excluded unless they were described by a relevant keyword indicating a clear climate mitigation link (Supplementary Table 17). Manual verification revealed that many of these ventures were technology firms with minimal or unclear climate relevance (for example, Airbnb). Second, startups were excluded due to lack of information if no sector or industry group was specified, the description or tags did not include any relevant keywords and no founding year was provided. Third, startups were excluded from the temporal or geographical scope of this analysis. Startups located outside of the United States were excluded. Startups founded before 2005, the year the first major global climate agreement (the Kyoto Protocol) entered into force, were excluded. When the founding year was not included in the i3 data, it was identified by the authors using previously cleaned data provided by Kurowski and Doblinger and publicly available information from databases such as Pitchbook, Crunchbase and OpenCorporates. Fourth, entities in the dataset were also excluded if they were determined to be a large group or corporation (for example, EON Group), a public agency (for example, the US Department of Energy) or a university or research institute rather than a startup. Finally, startups were excluded from the analysis if they had not received a single investment or grant during the 2005-2020 period.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 78}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Stefanelli and Lukac (2020)67 provide a framework for conducting power analyses for conjoint experiments using simulation techniques. Using their online power-analysis tool (https://mblukac.shinyapps.io/conjoints-power-shiny/), we find that experiment 1 is well powered. With 894 participants, 5 tasks and 4 variable levels (attribute with the largest number of options), the experiment has 94% power to detect an effect of 0.05 and 81% power to detect an effect of 0.04. Experiment 2 is not as well powered given the smaller available sample size of local elected officials; with 206 participants, 4 tasks and 4 variable levels, the experiment has 42% power to detect an effect of 0.05 and 78% power to detect an effect of 0.07 (Supplementary Fig. 6).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 79}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The quantity of interest in our analyses is defined as the percentage by which the network costs differ between the reference scenario and the alternative scenarios, and we refer to this quantity by: \u0394 = - x i j ir , , , i j j C C C 100 , ir where Ci,r is the annual network costs of household i in the reference scenario, while Ci,j stands for i' s costs in the jth alternative scenario, and \u2208 (f100, e100, f50 pa50,f50 e50,f50 pm50,pa100,pm100,f pa e, pa50 e50,pm50 e50,f pme). A negative sign of \u0394i,j therefore indicates a cost  reduction under the alternative scenario j compared with today's regulatory practice, while a positive sign points to increased costs for household i. To investigate which household characteristics are associated with cost savings or incremental costs under the different alternative scenarios, we estimate \u0394i,j with a linear regression model. Thereby we consider that \u0394i,j is a function of householdlevel characteristics x 1, \u2026 \u2026\u2026 , , , , , x x i ki ki , , , s uch that: i j = +\u2026+ + \u0394 \u03b2 \u03b2 \u03b5 , 1, 1, i j x x (2) , , ki kj i j , where \u03b2k,j holds the incremental average percentage points by which the network costs change when alternative scenario j is applied instead of the reference scenario, when household characteristic k increases by one unit. \u03b5i,j references the error term. All regressions presented in this study estimate equation (2).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 80}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Data were collected during October 2021 to February 2023 and included review of 1,159 regulatory documents (284 of which are legal documents used for protection coding). Our review focused on consumer-facing electricity retail regulation (such as the NERL) as opposed to energy regulation more broadly (such as the NEL). Where categories of interest for electricity services fell within distributor remit (that is, solar connections), we reviewed the appropriate documents associated with electricity regulation (such as the National Electricity Rules made under the NEL). We mapped 12 categories, four of which were combined into a single indicator ('minimum complaints protections'). Data collection was completed during October 2021 to February 2023 and included review of 284 legal documents to identify protections in each settlement. Regulatory environment at the settlement level was cross-checked with review of over 800 further documents to ensure no exceptions were overlooked. Settlements were coded based on their legal protections up to and including 1 July 2022. Regulation undergoes frequent iteration, and there were numerous pending changes proposed in draft form or in the process of introduction during our review (notably in remote WA, though this is unlikely to change community status in the short term; Supplementary Note 6).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 81}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used RD to estimate the impact of changes in the injunctive feedback included in the neighbour comparison. We justified this approach by showing that customers who received one, two or three thumbs up within the April-May 2018 eHER were different in many respects, which may also correlate with the impact of the treatment (Supplementary Table 10).  The RD approach allowed us to eliminate the influence of confounding factors on the estimated effect of changing the feedback category, as it focused on customers for whom the number of thumbs up is random. The price we paid for the improved identification of the effects is that the impacts estimated through RD are local, specific to a neighbourhood of the thresholds.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 82}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To take broader social trust into account, respondents were asked a common survey question on social trust: \u201cGenerally speaking, would you say that most people can be trusted, or that you can't be too careful in dealing with people? Please tell me what you think, where 1 means you can't be too careful and 5 means most people can be trusted.\u201d In the analyses, an indicator of the lowest level of trust was contrasted with a set of dichotomous indicators for each of the other categories of trust. Ancillary analyses showed that community and generalized trust were not substantially correlated, suggesting that each were distinct indicators of trust.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 83}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The fully randomized design allows us to simultaneously estimate the causal effects of multiple treatment components based on simple linear regression26. Hence, average marginal component effects (AMCEs) were calculated using a simple linear regression estimator with standard errors clustered by respondent, using Stata 14.2 (by StataCorp, see https://www.stata.com/stata14/). The dependent variable is based on the rating scale, and the models include sets of dummy variables for the values of all attribute levels. To ease interpretation of the results, we dichotomized the obtained data with the rating scale using the median (which is 4) as the cut-off value. The resulting dependent variable 'Phase-out Support' is hence coded 0 for cases where a respondent rated a proposal as poor to neutral (1 to 4) and 1 for cases where (s)he rated a proposal as positive (5 to 7). The rationale for using the rating outcome as the dependent variable (instead of the forced-choice outcome) is that it may allow for a more fine-grained assessment of preferences. In the first task (forced choice), respondents had to choose one out of two scenarios in each of eight rounds. However, the comparison of scenarios may include instances where respondents have either strong preferences for or against both proposals\u2014a situation that cannot be meaningfully ascertained by a forced-choice outcome. By contrast, in the rating task respondents could appraise both scenarios independently and on a more fine-grained scale. Nevertheless, replicating the analyses based on the forcedchoice outcome leads to substantively the same results (see Supplementary Fig. 2).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 84}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    For the second set of models for the week-byweek allocation of vaccine doses, we present a series of hierarchical linear growth models (Raudenbush and Bryk 2002; Singer and Willett 2003) with a correction for spatial dependency using a queen contiguity spatial weight matrix (Savitz and Raudenbush 2009). Given the nested structure of the data, weekly allocations per ZIP code, we used this approach to model the cumulative change over time in the number of vaccine doses per ZIP code. However, because the data were still organized by physically adjacent spatial units of analysis at Level 2, we used Savitz and Raudenbush's (2009) routine to account for spatial dependency using HLM 8.1, which is an approach used in similar health research  (O'Connell 2015). These results can be found in Table 3.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 85}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We searched the US Patent and Trademark Office website for patents assigned to each cleantech startup, issued on or before April 20, 2017. Design patents were excluded from the dataset. Observations were manually reviewed if the name of the assignee was not an exact match for the name of the company, or if the year of the patent filing was prior to the recorded founding year of the company. Patents are counted by the year in which the application was filed. Observations were collected through December 31, 2014, to account for the lag in observing a successful patent application. A citation-weighted count was also generated, following Trajtenberg's method of adding the annual patent count to a sum of all forward citations to those patents56. Citations to patents were observed through April 1, 2017.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 86}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We fielded an online survey of 1,050 Swiss residents, quota sampled on age, gender and language, in December 2019. The survey was provided in German and French but not Italian, which is the official language in the canton of Ticino as well as some municipalities in Graub\u00fcnden. Nevertheless, the survey covers respondents from all Swiss cantons. Overall, the sample quite closely matches the Swiss population; however, as typical for such surveys, the groups of the lower educated (secondary education I) as well as the oldest age groups are somewhat underrepresented (Supplementary Section 26). A copy  of the Swiss survey instrument is also provided in Supplementary Section 26.  The survey received a human subjects review from the University of California Santa Barbara's Office of Research Human Subjects Committee (protocol number 21-19-0801). All survey respondents provided informed consent before beginning the survey.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 87}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    This paper discusses the uncertainty of the simulation results from five aspects: the baseline scenario, mitigation policies, model parameters, energy storage technology and carbon sequestration capacity. First, China's carbon dioxide emission pathway may present varying predictions under the baseline scenario (Supplementary Section 3) and the strictness of achieving the mitigation target directly impacts emission reduction and economic costs. Thus, we set two scenarios for accelerating and delaying the emission reduction progress in the baseline to test this uncertainty. Second, different intensities of mitigation policies may lead to a nonlinear changing trend or turning point for reduced emissions and economic losses. To test this uncertainty, we created 1,295 scenarios by combining different policies with different intensities on the basis of an extensive literature review (Supplementary Section 3.2). We also developed two additional policies with more stringent intensity (grade 6) and weaker intensity (grade 0). Third, the simulation results for achieving the carbon neutrality target may be affected by the substitution elasticity between different energy products in the model. To address this uncertainty, the substitution elasticity between energy products was increased or reduced by 25% to test the robustness of the results. Fourth, energy storage technology can additionally support the growth of high proportions of renewable energy and increase the economic cost. In this paper, we set two scenarios with high-cost and low-cost storage energy development to test the robustness of the simulation results. Finally, enhancing the carbon sequestration capacity is crucial for achieving carbon neutrality goals, as the percentage of scenarios in which the carbon neutrality target is achieved by 2060 will decrease substantially from 11.1% to 0.23%, with a decrease in the carbon sequestration capacity from 2.5 GtCO2 to 1.5 GtCO2 (Supplementary Fig. 22). In this study, we assumed that the capacity is limited to a maximum of 2 GtCO2 from CCS technology and forest systems by 2060. On the basis of the five categories of uncertainty analysis above, we find that the trade-offs and synergies between mitigation policy pairs remain robust: the simultaneous implementation of policies with R and E at high levels has notable positive impacts on all dimensions, and the policy combination with C and R has notable negative impacts on all dimensions. See Supplementary Section 6 for details about the uncertainty analysis.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 88}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The data used in this paper were sourced from the NT Government owned utility Power and Water Corporation, the Australian Bureau of Meteorology (BOM) and the Australian Bureau of Statistics. Daily electricity use data for 3,300 households with a smart prepayment meter were matched to temperature data from the closest weather station. For cases where there were no temperature data for that day, the next closest weather station was used (6.1% of all observations). If that still resulted in a missing value, then the average for that climate zone was used (0.3% of observations). Data on disconnections were provided along with the time and date that the electricity service was discontinued and subsequently restored. These cases of disconnection were aggregated into daily data and separated into two variables on the basis of whether an electricity service was restored to the household on the same day or not. Selected summary statistics for these data by climate zones are shown in the paper in Tables 1 and 2.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 89}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The study's communities, both midsized cities in the same large metropolitan area (U.S. Census Bureau 2017), were middle- to upper-middle-class. They were demographically quite similar, with median household incomes close to the state average and high proportions of residents identifying as White. Middle-class Springfield was more socioeconomically and ethnically diverse than uppermiddle-class Greenville; its median housing value was half as high, and half as many residents had a bachelor's degree (U.S. Census Bureau 2017). Both communities had unusually high rates of positive health behaviors and low obesity rates and were located in a geographic region that was considered a politically liberal health mecca attracting highly educated new residents.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 90}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    In scenarios with explicit land-protection schemes (protForest, protForest90%, protPrimforest, protBH, protCPD, protFF and protLW), we removed the respective areas from the land pool that is potentially available for any agricultural activities (Supplementary Figs. 3-9). In protForest, all primary and secondary forests are protected (3,683 Mha in total); in protForest90%, only 90% of the forests are protected in each simulation unit (3,315 Mha in total; Supplementary Fig. 10 shows the MAgPIE simulation units); and in protPrimforest, only primary forests are protected (1,339 Mha in total). The other land-protection policies affect only some focus areas. In protBH, biodiversity hotspots are protected (909 Mha); in protCPD, centres of plant diversity are protected (651 Mha); in protFF, frontier forests are protected (1,084 Mha); and in protLW, last of the wild areas are protected (3,635 Mha)64. Additionally, in all scenarios, specific land areas are protected or dedicated for afforestation according to the Nationally Determined Contributions targets of the nations that are participating in the Paris climate agreement (Supplementary Fig. 11).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 91}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Data are from households that participated in a pilot programme administered by a southwestern US electric utility. The utility sent invitations by direct mail and email soliciting opt in to the 2016 TOU pilot to roughly 197,000 households, 14% of which opted in. Some households that accepted the offer were not enrolled because they were ineligible (for example, were already participating in a special rate programme). The utility randomly assigned 21,534 households to either TOU1 (n = 4,709), TOU2 (n = 6,365), TOU3 (n = 3,746) or the control group that opted in to TOU but was not placed on a TOU rate (n = 6,714). Lowincome households and those with elderly members were deliberately oversampled for TOU2. TOU3 was not fully rolled out by the start of the study period, due to additional complexities unique to the rate, and so could not be included in the present study; we consider only TOU1, TOU2 and the control group\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 92}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The NECPs anticipate dramatic changes in the installed generation capacity of European countries (Supplementary Section 2). We use 2024 as the reference year for the current capacity mix because this allows us to acknowledge generation capacity that is very close to coming into market or to closing. Countries' plans foresee the doubling of variable renewables (wind and solar) from slightly above 500 GW to more than 1000 GW by 2030. Solar PV would experience the largest absolute growth, with the addition of more than 300 GW in this decade, whereas wind turbine capacity would increase by more than 230 GW (Supplementary Section 2 provides details). The plans also envision additions to hydropower capacity, battery storage and demand-side response, but on a much smaller scale. As for the retirements, all fossil fuel technologies experience reductions in capacity by 2030 in the NECPs, with coal being the most affected\u2014capacity would be reduced by 41 GW, so that by 2030 coal power plant capacity would be approximately halved. The closure plans of nuclear plants in several countries would also lead to a sharp reduction total deployed capacity in this technology by 2030. Whereas there are important differences in scale across countries, the broad trend towards substitution of fossil fuels and nuclear with variable renewables is common to all countries. The NECPs also reflect a large expansion in the interconnection capabilities of European markets, which is also a driving factor of price formation. All interconnector projects in NECPs and the ERAA have been modelled (Supplementary Section 3).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 93}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    It is assumed that a strong increase in the use of electric vehicles reduces liquid fuel demand in land transport to zero, hence reducing the need for biomass and/or electricity for meeting renewable fuel targets (land transport demand overall is assumed to increase by 20%). A liquid fuel demand is however retained in aviation (total fuel demand increases by 70% compared to 2011), shipping (+50% compared to 2011, with half of the fuel demand supplied by hydrogen) and in the chemical industry (same demand as 2011), which can be supplied through solid biomass-based liquid fuels (biofuels), electrofuels, electrobiofuels and fossil fuels. Transport and chemical demand is assumed as for the year 2060 in Millinger et al.11, and recycling of plastics is not considered.For a sensitivity analysis with less sector coupling, the following options were turned off completely: battery electric vehicle (BEV) charging demand-side management; vehicle to grid; thermal energy storage; waste heat usage from biofuels, electrolysis, DAC and BioSNG; H2networks; H2underground storage in salt caverns. Further, no expansion of the electricity transmission or district heat grids from 2022 levels was allowed.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 94}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Hector is the reduced-form carbon-cycle climate module that is available for use in GCAM15,71 and is an open-source model. This study is based on Hector v.2.5. Hector has a three-part carbon cycle: one-pool atmosphere, three-pool land and four-pool ocean. The model's terrestrial carbon cycle includes primary production and respiration fluxes while also accommodating arbitrary geographic divisions, such as ecological biomes or political units. Hector's ocean component includes a detailed representation of the inorganic carbon cycle, calculating air-sea fluxes and ocean pH (ref. 71). Hector reproduces the global historical trends of atmospheric CO2 , radiative forcing and surface temperatures. GCAM interacts with Hector through emissions. At every time step, emissions from GCAM are passed to Hector. Hector then converts these emissions to concentrations when necessary and calculates the associated radiative forcing, as well as the response of the climate system (for example, surface temperature and carbon fluxes).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 95}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We obtained BEV-specific data (see Link et al.58), comprising sales data and comprehensive information on installed batteries until 2022, from the Fraunhofer ISI xEV battery database. Based on these data, we calculated sales-weighted average battery capacities per segment and BEV-specific segment splits covering the EU, EFTA and the UK. The gross battery capacities were derived by assuming an average share of usable energy of 93% (ref. 59). The segment-specific BEV energy consumption was calculated on the basis of European CO2certification data, as prescribed under Regulation (EU) 2019/631 and provided by the European Environment Agency60. We evaluated all vehicles with specific CO2emissions of 0 gCO2e km-1 (by the World Harmonized Light Vehicles Test Procedure). These data are available up to 2022 and cover the EU, the United Kingdom (until 2019), Iceland (from 2018) and Norway (from 2019). We assumed energy consumption improvements of at least 5% until 2030-2035 due to increased energy efficiency or road load reductions. The latter mainly concern lightweight materials and decreasing battery weight61-63 as there is increasing evidence that higher specific energy levels and enhanced system integration overcompensate increasing battery sizes.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 96}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Accelerated aging. To calculate the speed of aging, we used an epigenetic clock known as the GrimAge index (Horvath and Raj 2018). The index is called GrimAge\u2014after the Grim Reaper\u2014because an accelerated score is grim news. This measure of aging has been shown to be a more robust predictor of morbidity and mortality among different racial groups than other epigenetic clocks currently available (Lu et al. 2019; McCrory et al. 2021). The index was developed by identifying a set of plasma protein predictors of mortality and then using these protein predictors to identify CpG sites that could predict time to death. As expected, the GrimAge index has a weak to moderate correlation with chronological age in the FACHS sample (r = .22), indicating a discrepancy between biological and calendar ages. Following standard procedures, we regressed GrimAge on chronological age to create a speed of aging score or \u201caccelerated aging.\u201d The resulting speed of Grim aging measure was thus adjusted to correlate with chronological age at 0. A positive value on this variable indicates, in years, accelerated epigenetic aging, whereas a negative value indicates, in years, decelerated aging.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 97}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To solve the equilibrium, we calibrated the model to the year 2016, which is the most recent year for the ICIO-AMNE (Inter-Country InputOutput, Activity of Multinational Enterprises) tables (https://www. oecd.org/sti/ind/analytical-amne-database.htm). We imputed bilateral trade and MP shares and consumption preference alphaj l from the ICIOAMNE 2016 data constructed by the OECD28, and set \u03b8 = 4.5 and sigma = 4  following ref. 12. The effective corporate tax rates for the different economies were obtained from the World Bank (http://www.doingbusiness.org/). The changes in the corporate tax rates of the different regions were obtained from KPMG (https://home.kpmg/xx/en/home. html). The country sectoral-level emission data were from ref. 29. The cost- minimizing problem faced by firms implies that \u03b2 j l = \u03c1le j il c j il q j il = \u03c1l\u03c5 j l , and therefore \u03b2 j l indicates the share of carbon revenue in output at the country and sector level. The national carbon revenue in GDP is therefore \u03c1l\u2211j ej l GDPl . To estimate \u03b2 j l , we first derived the share of the energy and carbon tax revenue in the GDP at the national level, utilizing the data from the OECD database. These data, combined with national emissions, yield the emission tax rate \u03c1l at the national level. Subsequently, multiplying this tax rate by the country-sector-specific emission intensity generates an estimate of \u03b2j l (Supplementary Information 11).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 98}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We examined trends in U.S. states' IOL rates using the National Vital Statistics Systems (NVSS) restricted birth data for years 1990 through 2017 (NCHS 2020).3 To reduce the confounding effects of multiparous women and multiple pregnancies on risk for obstetric interventions (Denona et al. 2020; Donahue et al. 2010), we restricted the analytic samples to include only singleton first births among non-Hispanic White, non-Hispanic Black, and Hispanic women (henceforth, White, Black, and Latina). The data are composed of 41,126,037 singleton first births: 26,446,616 to White women, 6,252,741 to Black women, and 8,426,680 to Latina women. We aggregated the data at the state level by mother's race-ethnicity to create separate analytic samples for births among states' White, Black, and Latina childbearing populations (for the creation of the analytic samples, see Figure S1 in the appendix in the online version of the article). Due to small counts of births, we omitted Idaho, Maine, Montana, North Dakota, South Dakota, Vermont, and Wyoming from the analytic sample for births to Black women, and we omitted Maine, Vermont, and West Virginia from the analytic sample for births to Latina women. The analytic sample for births to White women is composed of all 50 states plus the District of Columbia (DC) across 28 years (1,428 state-years), and the analytic samples for births to Black and Latina women were limited to 43 states plus DC (1,232 state-years) and 47 states plus DC (1,344 state-years), respectively.4\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 99}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We conducted a comprehensive, structured and fully documented data quality validation of the green hydrogen project announcements, manually validating 524 project entries across all three database versions. For projects announced for 2022 or 2023, we covered at least 90% of the announced capacity, while for projects announced for 2024-2030, we covered at least 75% of the announced capacity in all three database versions (Supplementary Table 1). In addition, we manually verified the fate of all projects announced to launch in 2023 in the database published in October 2023 (Fig. 3). Note that we did not attempt to identify missing projects, implying that the success rate may change if projects that were realized in 2023 were missing from the most recent database version included in this analysis, published in October 2023. During the data validation, we adjusted the size of a project if it was not operating at its nameplate capacity, which was the case for the world's largest green hydrogen project, Sinopec Kuqa in China. The data quality validation procedure is described in detail in Supplementary Note 1.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 100}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We focused on three key dependent variables measured when respondents were ages 60 and older. First, self-rated health was a five-category indicator ranging from poor (1) to excellent (5). Second was the number of reported current or former chronic conditions. Following the logic used by Brady et al. (2022), we focused on life-threatening conditions: high blood pressure, cancer, diabetes, heart attack/ disease, lung disease, and stroke.3 Third, we constructed a scale of seven activities of daily living (ADLs) that represent functional limitations: whether the respondent has difficulty bathing, dressing, eating, getting in and out of a bed/chair, going outdoors, using the toilet, and walking.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 101}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We tested hypotheses for the current study by employing data from the Family and Community Health Study (FACHS). FACHS is designed to investigate the factors associated with the health and well-being of African American adults (see Lei et al. 2018; Simons et al. 2019). The FACHS sampling strategy includes African American families with a child who was in fifth grade at the time of recruitment. Families were intentionally recruited from neighborhoods that varied on demographic and economic characteristics based on 1990 census data. For 259 census block groups (115 in Georgia and 144 in Iowa), households were randomly selected from rosters of fifth graders in the public school system. Households were then contacted until the required number of households were recruited (84% response rate).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 102}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our dependent variable was the annual drug-related mortality rate per 100,000 people by state. We obtained these data from CDC WONDER's (CDC 2018) multiple cause of death database. As defined by the CDC, drug-related deaths are those that are unintentional (ICD-10 codes X40-X44), by suicide (ICD-10 codes X60-X64), by homicide (ICD-10 code X85), undetermined (ICD-10 codes Y10Y14), and all other drug-induced causes (deaths not categorized in any of the aforementioned ICD-10 codes).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 103}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The river system infrastructure and economy-wide simulators were connected using a generic co-evolutionary framework developed in a previous study7. The framework enables linking river system simulation models (with daily or monthly time steps) with dynamic-recursive annual CGE models. At each annual time step, the coupling framework performs an iterative bidirectional communication between the river system and the CGE simulators to ensure coherence in the annual national-scale irrigation water supply and demand, municipal water supply and demand, hydropower generation, non-hydro generation and capacity, and electricity demand. In each iteration over an annual time step, the river system model quantifies and spatially aggregates national-scale irrigation and municipal water supplies and hydro and non-hydro generation on the basis of the river system's spatial and temporal constraints, infrastructure, and external drivers. This information is then passed to the CGE models as an external shock on the basis of which changes to the economy's municipal and irrigation water demands, electricity demand, and non-hydro capacity are determined and passed back to the river system model for the next iteration. Iterations over each annual time step can be terminated by a maximum number of iterations and/or a convergence error. In this work, we specified a maximum of three iterations between the river system and the economy-wide simulators for each annual time step and a convergence error of US$5 million measured using the Ethiopian real GDP. The coupling framework is implemented using the open-source Python Network Simulation framework81. The reader is referred to Basheer et al.7 for further details about the co-evolutionary coupling framework used in this study.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 104}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Data were collected by YouGov. YouGov uses their proprietary panels and proprietary sampling technology. YouGov begins by framing quotas on the basis of the census of the named populations. This frame is the basis on which the sampling software controls the flow of members into each survey. The sampling system will randomly select from each panel and allocate to surveys according to the quotas set. Panellists receive an invitation email containing a survey link. When they access the link, the router checks against quotas on all live surveys and allocates them to a survey they qualify for.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 105}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We utilized CDC restricted access mortality files from 2000 to 2016. The database contains every death in the United States in each year. Cause of death codes allowed identification of drug overdoses, which we then aggregated to the county level. We calculated age-adjusted overdose rates per 100,000 for each county. Unlike public use data, restricted data contain no suppressed information, which permits more precise analysis of counties with fewer than 10 deaths per year.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 106}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Education was measured in years ranging from 0 to 25.2 We included a squared education term to account for diminishing returns to education (Bracke et al. 2014). Household occupational status translated ISCO-88 occupational codes in the 2006 survey wave and ISCO-08 occupational codes in 2012  and 2014 surveys into the International SocioEconomic Index of Occupational Status (ISEI) scale (Ganzeboom and Treiman 1996) utilizing the updated ISEI-08 coding (Ganzeboom 2010). The ISEI index was applied to the respondent's reported occupation and, if indicated, their partner's occupation returning the highest score ranging from 1.10 to 8.90. Finally, household income was calculated in deciles for both survey years and ranges from 1 to 10.3\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 107}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We coded all participant observation, interview and content analysis data using an iterative qualitative process of inductive coding. We first coded the data according to emergent themes revealed by each source independently (that is, participant observation notes, interview transcripts and policy documents). We then conducted multiple iterative rounds of focused coding to homogenize our analysis across all data sources. The final coding protocol included the following themes:  (1) justice contestations; (2) the implementation process; (3) implementation decisions and outcomes; and (4) implementation challenges. The final coding protocol can be found in Supplementary Appendix D.  We used NVivo 20 software for all coding.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 108}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The representation of the NDCs in our central pathway is based on ref. 5 and is explained in detail in the supplementary information to that study. This study also includes 21 new and/or updated NDCs after 30 September 2021, including those from China, Pakistan and many African and Middle Eastern countries that were not included in ref. 5 (Supplementary Table 5). We assume that the NDCs are achieved as stipulated and focus on the climate outcomes of their successful implementation. Examining the likelihood of individual regions achieving their submitted targets is beyond the scope of this study. Our representation includes only ratified and quantifiable unconditional NDC commitments, including absolute emissions limit, percentage emission reductions from a given reference level and emission intensity targets. Parties whose commitments included: (1) only actions/policies, (2) non-GHG targets with no corresponding GHG emissions target or (3) only sector-specific GHG emissions reduction targets without attempting to quantify the impact on their overall GHG footprints are assumed to have target year emissions equal to the GCAM emissions in the default reference scenario without any climate policy ('Reference\u2014No Policy' in ref. 5). Likewise, in cases where a country's 2025 and 2030 emissions based on its NDC are lower than the default reference scenario in the same year, the NDC emissions are assumed to be achieved as stipulated. In cases where a country's NDC emissions are higher, emissions are assumed to be equal to the reference scenario. For countries that included multiple types of commitments in their NDCs, such as economy-wide emissions reductions backed by sectoral policies or targets, only the broadest commitment was considered. For example, China's NDC representation in GCAM is based on its commitment to reduce its carbon intensity of GDP by 65% relative to 2005 and it does not explicitly model its targets for non-fossil energy consumption or increased forest stock.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 109}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    . Most feedback devices display a bundle of elements rather than a single numeric metric52 to put the measurement data into context; frequently used elements include historic comparisons, peer comparisons, analogies and energy savings tips. Likewise, the smart shower meters in rooms assigned to the treatment condition displayed water consumption in litres (one decimal), energy use in (kilo)watt hours, current water temperature, a dynamic rating of the current energy-efficiency class (A-G) and a four-stage animation of a polar bear standing on a melting ice floe with stage transitions at predefined Articles energy use thresholds. The energy consumption displayed on the screen represents the lower bound of the energy used (without losses), and is calculated using the standard engineering formula for heat energy (Q = m xcp x \u2206T, with heat energy Q, mass of water m, heat capacity cp , and \u2206T being the difference between the measured water temperature of the ongoing shower and the average cold-water temperature). In the analysis of energy savings, we take into account the same average heating efficiency and losses as in Tiefenbeck et al.25. The energy-efficiency class displayed was inspired by the (static) energy-efficiency class scale indicated on household appliances in Europe. The smart shower meter dynamically indicates the energy efficiency of the current shower based on the energy use in the ongoing shower, starting in energy efficiency class A and progressing to B, C and so on at predefined kilowatt hour thresholds; the thresholds were defined on the basis of the distribution of energy use per shower in a pilot study. The four stages of the polar bear animation are tied to the energy-efficiency class, and change with the transitions from B to C, D to E and E to F, respectively. While the polar bear may be an eye-catching and memorable display element, it does not seem to drive the savings effects. A related study specifically examined the effect of variations of the design choices of the feedback elements; the results indicate that if the polar bear animation makes any difference, it reduces rather than increases the effectiveness of the display52.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 110}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Data from the Cleantech Group i3 database on startups, investors, initial public offerings (IPOs), mergers and acquisitions, and corporate relationships was accessed on 19 January 2022. These proprietary data are available to subscribers at https://i3connect.com. The Cleantech Group data are used in other major reports such as the International Energy Agency's (IEA) Tracking Clean Energy Innovation Report and the Silicon Valley Bank's The Future of Climate Tech Report8,38,39. In addition, it has been previously used in multiple peer-reviewed research papers3,9,10. Given the extensive use of the Cleantech Group's i3 database in prominent reports and peer-reviewed papers and the fact that information in the database is regularly updated by the database provider's research teams or by the firms themselves (with the last updated year reported), to our knowledge, it represents the most thorough dataset available for climate tech.The raw data had 38,089 startups and 17,737 investors worldwide. Each startup has information on sector, location, founding year, current status (for example, public, private or bankrupt), a description of the startup activity and keyword terms associated with the startup.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 111}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    All data processing, analysis and plot generation were carried out in the R platform48. Details of the code and the packages used are provided in Supplementary Codes 1 (National\u2014state-level variance) and 2 (Sub-district\u2014Koppal) hosted on Figshare45,46. The raw data collected in MS Excel format from the distributor terminals were first processed by the field staff of a partner organization\u2014SAMUHA\u2014in accordance with the Institutional Review Board guidelines of the University of British Columbia. In addition to deleting names, and other personal identifiers (different from the unique 16-digit number provided by OMCs), the first 10 characters of the address were scrubbed. The anonymized dataset was then transmitted online to the research team. We used a series of codes in R to join datasets and format them for further analysis.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 112}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    First, we calculated descriptive statistics for the statelevel measures and individual-level measures. For the individual-level descriptive statistics, we stratified by gender and estimated t tests for continuous variables, test of proportion for dichotomous variables, and chisquare tests for categorical variables to understand statistical differences between men and women. Then, we stratified the sample by gender and ran several multilevel logit models, with individuals nested within states, for each health care service. These models predicted the use of each preventive health care service as a function of state-level structural sexism exposure. Each model included all previously mentioned state-level and individual-level covariates. We retained the largest sample size for each outcome, which means that the sample size varies depending on how many individuals responded to each question. The sample sizes range from 115,012 to 182,582 for women and 95,317 to 159,469 for men.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 113}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    From the U.S. Census Bureau's American Community Survey (ACS) and decennial censuses, we included county-level time-varying covariates, specifically population density, median household income, and percentages foreign-born, female-headed households, non-Hispanic Black, Hispanic, and over 25 with a bachelor's degree. We included an interaction between percentage foreign-born and Hispanic given their high correlation and a significant interaction effect in several model specifications. To include all counties, we required 5-year ACS estimates because only larger counties are available over shorter estimates. Because these begin in 2009, we linearly interpolated years between the 2000 census and 2009 (with the exception of population density because estimates are available annually). We also included county-level unemployment rate, available annually from the Bureau of Labor Statistics. From the Annual Survey of State Government Finances, we included state-level per capita spending on education, public welfare, hospitals, and health.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 114}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We estimated large-scale infrastructure failure aggregated by plant category. We derived the temperature, at which the largest increase in outages occurred for each power plant category, from the 2021 outage data (Supplementary Figs. 4-7). Furthermore, we estimated a constant outage level in terms of tripping capacity. Finally, we also defined a constant recovery rate, which describes how outages decrease after the recovery temperature is reached. This approach will omit smaller outages, but it accounts better for the inter-dependency of failures. Furthermore, the uncertainty in the data did not allow us to derive outage curves for individual plants. A detailed outline of how we derived the outage parameters from the 2021 data in Texas is given in the Supplementary Methods. The resulting outage models were applied to the 71 years of climate data to obtain the capacity availability during this period.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 115}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    A total of 160 participants were recruited for the study. Participants were recruited online using Prolific Academic and through the Reddit 'Climate Change sceptics' group. Participants were screened on Prolific using two questions: (1) 'What is your nationality?' (only participants who answered 'United States' to this question were eligible to participate) and (2) 'Do you believe in climate change?' (people could answer: 'Yes', 'No', 'Don't know' or 'Not applicable/rather not say'; an equal number of people saying 'Yes' or 'No' were recruited). Participants' location within the United States varied and spanned areas that are deemed high and low for their support for climate change science59 (Supplementary Fig. 1). To ensure that participants beliefs about climate change were consistent with the earlier Prolific screening, we added an additional filter question ('Global warming refers to the idea that the world's average temperature has been increasing over the past 150 years and may be increasing more. Do you think that global warming is happening?'; Answers: 'Yes', 'No' and 'Don't know'). Only people who responded 'Yes' or 'No' were included in the study. Seventeen participants were excluded from the analysis, broken down as follows: three were excluded because they did not complete the required surveys, five because they failed an attention check question in either the pre-/post-survey and nine because they did not fulfil the requirement to use the entirety of the allotted US$20. Of the 143 remaining participants, 73 were used as controls (35 believers, 38 sceptics) and the remaining 70 were used as the treatment group (35 believers, 35 sceptics). Supplementary Table 5 provides a breakdown of all participants' demographics.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 116}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We further tested the sensitivity of our results by performing separate analyses of Cleantech 1.0 (startups founded 2005-2011) and 2.0 (startups founded 2012-2020) investment periods and by examining the difference between startups that exhibit high-patenting activity vs low-patenting activity. High patenting was defined as being in the top decile of startups in terms of number of patents (greater than 12 patents). The results of these analyses are provided in Supplementary Tables 13-16.These robustness and sensitivity analyses attempted to account for as many factors as possible. However, other potentially relevant variables were not included in this analysis due to lack of data availability, which is a common problem due to a widespread focus on secrecy in competitive startup sectors, or difficulty accessing granular data for the large numbers of entities included in this analysis. If data were available, future research could include considerations such as relationships with founder networks, public-private partnerships3, proximity to local branches of a corporate investor21, degree of digitalization34, startup size and generalizability to other sectoral and country contexts.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 117}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We measured the population at risk of hunger, or the number of people whose food availability falls below the mean minimum dietary energy requirement, on the basis of previous studies51-53. The following four parameters were used: the mean minimum dietary energy requirement, the coefficient of Nature Climate ChaNge variation of the distribution of food within a country, the mean food availability in the country (kcal per capita per day) and total population. Minimum dietary energy requirements are exogenously calculated on the basis of demographic composition (age, sex) of future population projections. Future changes in the inequality of food distribution within a country are exogenous and follow projected national income growth. This is based on an estimated relationship between income and the coefficient of variation of food distribution with observed historical national-level data. Poor infrastructure, remoteness and a high prevalence of subsistence farming limit local markets in distributing food equally across households7. Income is lowest in SAS and SSA, regions in which the share of land under subsistence farming is the largest (27% in SAS and 43% in SSA)54. Food availability in kcal per capita per day is endogenously determined by GLOBIOM at the regional level. One limitation of the approach is that it does not include within-country distributional consequences of trade integration and/ or climate change through income effects. Trade policies and climate change alter food prices, which affects individual incomes, purchasing power and food access depending on households being net consumers or net producers of food33. At the aggregate regional level, the bias from not considering these distributional effects may be upward or downward, depending on the share of net-consuming versus net-producing households; degree of subsistence farming versus agricultural wage work; and share of rural versus urban population in each country.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 118}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Twenty climate projections were selected from CMIP6 Tier 1 GCMs on the basis of uniform sampling to cover the full range of available SSPs, radiative forcing and the joint distribution of EOC change in precipitation and temperature over the Nile Basin. Processing, downscaling and bias correction of the GCM simulations were driven by the requirement for transient (2017-2100) three-hourly forcing data across seven climate variables that govern the surface mass and energy balances in the hydrological model (described in the next section). The seven variables are precipitation, temperature, incoming shortwave radiation, incoming longwave radiation, humidity, wind speed and surface pressure. Given the large spatial domain, the low availability of subdaily model output for all of the relevant variables in CMIP6 and challenges of multivariate bias correction51, we derived bias-corrected transient projections by (1) resampling the 0.25\u00b0 historical baseline climate dataset to match the (detrended) relative variability of the selected GCM projections and then (2) applying perturbation factors to reintroduce the change signal extracted from the GCMs following a quantile delta mapping approach52.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 119}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Given a fixed configuration of capacities for a set of zones (country/areas in our implementation) and transfer capacities across zones (interconnections in our implementation), GenX's dispatch algorithm minimizes the total variable costs of satisfying each zone's demand at each of the 8,760 h in the year. The variable costs of each technology include a non-fuel variable operating cost plus a fuel cost, which is defined in turn by the fuel price per thermal MWh and the thermal efficiency of each plant type. GenX allows for the simulation of storage technologies, including hydropower plants with reservoirs and/or pumping capabilities and batteries. Because the algorithm minimizes the total annual cost, the resulting solution assumes perfect foresight of hourly profiles for capacity factors, inflows and demands for the full year. Hence, batteries and reservoirs will be charged and discharged in the optimal dispatch solution provided by GenX at the times that minimize the total cost of electricity generation for the full year. GenX includes the possibility to curtail demand if the cost of satisfying it exceeds a pre-set value of loss load parameter (set at 3,000 euros in our analysis). GenX also allows for demand-side response capabilities, which allow to anticipate or delay certain loads at a cost. The full solution of GenX dispatch is characterized by hourly generation profiles for each technology in each country/area and the hourly electricity flows across countries/areas (given the restrictions imposed by network capabilities). The Lagrange multiplier associated with the increase of 1 MWh in demand for a given country at a given hour is also calculated. Any technology in the model can set the marginal price, including variable renewables, storage, interconnectors or demand-side response.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 120}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our analysis involved several dependent variables that measured the use of preventive health care from BRFSS. Several of these BRFSS variables have different versions that factor age of respondent and frequency of use of the service. For these measures, we analyzed the versions that included the largest sample sizes to provide the most complete picture of gendered patterns of health care use. For example, there were two versions of the question about mammograms: (1) women who have ever had a mammogram and (2) women age 40+ who have had a mammogram in the past 2 years. We used the former measure because the 2018 mammogram recommendations vary for women 40 years and older, and therefore, the latter measure may miss important variation by limiting the time period. Most health care services apply to both men and women; however, there were three that were asked only of women and one that was asked only of men (described in the following). All respondents were asked about a variety of health care services. These included dichotomous measures of whether respondents had a person they thought of as their personal doctor, if they had ever had a colonoscopy/sigmoidoscopy or been tested for human immunodeficiency virus (HIV), and whether within the past year they had visited a doctor for a routine checkup, gotten a flu shot, or visited a dentist, dental hygienist, or dental clinic. For women, they were also asked if they had ever had a mammogram, pap test, or human papillomavirus (HPV) test. For men, they asked if they had ever had a prostate-specific antigen (PSA) test. All variables were coded 0/1 so that 1 indicated the participant had used the health care service within the specified timeframe.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 121}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Interviews were recorded and transcribed verbatim. Data were coded and analyzed using Atlas.ti. Participants were given pseudonyms to protect their identity. Data were analyzed inductively following a grounded approach (Charmaz 2014). Interviews first underwent open coding. During the initial coding phase, I simultaneously created detailed memos reflecting on my impressions of the emerging codes and patterns. These memos and initial codes guided the next stage of focused coding, during which new codes were created to capture salient themes within and across interviews and initial codes were condensed (Charmaz 2014). For the purposes of this analysis, I focused on data from medical providers and themes that emerged from codes relevant to drug testing, clinical decision-making, medical surveillance, risk, and collaborations between medicine and child welfare. Ethical approval was obtained through the appropriate institutional review board.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 122}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    A diverse research team of five conducted and analyzed the interviews, collaborating to construct a rigorous analytical process. Codes were developed inductively, similar to a grounded theory approach, through an iterative process of reading transcripts to identify patterns and themes, many of which centered around questions that we posed to participants, such as if and how they counsel patients from different backgrounds about contraception (Charmaz 2014). We then entered codes such as \u201cspecific contraceptive for specific patient\u201d into a qualitative research software program and further refined them into hierarchical coding schemes using line-by-line  coding. Given the semistructured nature of the interviews, findings for this article around providers' efforts to minimize and manage bias emerged unprompted during the interviews when providers were asked about their approaches to patients. We then ensured that all examples fit the codes and subcodes. To maintain consistency, researchers reviewed transcripts in pairs for intercoder reliability and continuously memoed throughout the coding process about relevant themes. All quotes used in this article were the most illustrative examples among many of the participants. Data were only included that were commonplace across participants. This research was reviewed and approved by state and university Institutional Review Boards. All names are pseudonyms.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 123}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Observations and attitudes towards novel marine-climate interventions were surveyed using an online survey-questionnaire targeting active practitioners. Questions were designed to capture observational data describing current arrangements for governing interventions and positional attitudinal data concerning perceived benefits and costs, gaps in governance, risks, and missed and emerging opportunities (see survey-questionnaire in Supplementary Table 8). Types of interventions used to design response options were identified from recent authoritative reviews15,34,84. The questionnaire used a mix of selected choice questions, ratings and open-ended text response questions. The questionnaire was delivered using Qualtricsxm online survey software. The survey instrument and specific questions were pre-tested by members of the research group, revised and then formally piloted through a soft launch of the survey in October 2022 with members of the study's technical advisory committee.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 124}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used probabilistic modelling of S-shaped production ramp-up and technology diffusion based on the latest empirical data to project future battery demand and domestic production in Europe, covering the EU, the European Free Trade Association (EFTA) and the United Kingdom. We also translated this battery demand into the corresponding amounts of required critical raw materials. This probabilistic approach captures the nonlinear propagation and simultaneous interaction of major parameters with inevitable uncertainties, in contrast to deterministic models that rely on single estimate inputs. However, the goodness of the projections still depends on the quality of the input data and chosen model parameterization. A Monte Carlo simulation (N = 1,000) then allows the construction of feasibility spaces and the classification of findings by probability. The model was implemented in Python. Model components and procedures are illustrated in Supplementary Fig. 1. We performed all calculations on a standard Lenovo notebook with an i7-8565U @1.8 GHz processor and 16 GB RAM (random access memory).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 125}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used regional fixed effects analyses to consider the impacts of predictor variables on billing, discomfort and the need for medical attention. By using regional fixed effects grouped by climate zone, these models control for unobserved time-invariant differences between households, for those differences associated with living in different climate zones. That is, the predictions of respective dependent variables in each regional fixed effects analysis are estimated conditional on the climate zone, and each climate zone is associated with a unique intercept.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 126}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    All model code and data used to generate results for this article are archived53 and a running version is available at https://github.com/Environment-Research/ revenue_recycling. The NICE model52 used here is a modification of the RICE model3,54, which was developed by W. Nordhaus. RICE is the regional counterpart to the global dynamic integrated climate-economy (DICE) model, which is one of three leading cost-benefit models used by researchers and governments for regulatory analysis, including to estimate the social cost of carbon55. RICE3,54 and NICE51,52 have been described in great detail elsewhere. Since their basic architecture is the same, we first describe this RICE architecture and then explain the model developments that make RICE into NICE, noting from the outset that all models of this class are reduced-form representations of reality with associated strengths and limitations56,57.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 127}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Energy insecurity and disconnection rates are likely to be determined by a range of factors, including the usual level of electricity use and the inability to pay. While we do not have household data on occupancy or income, we are able to categorize the meters into groups using average daily electricity use. The average daily load will be a function of the types of appliance, intensity of use and the number of residents. The percentile groupings used are shown in Supplementary Table 14 along with the aggregate expenditure on electricity. Note that the data are not a balanced panel due to the incremental roll out of smart meters across communities and we excluded those meters with less than 100 observations.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 128}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The price elasticity of global oil supply is low (close to zero) in the short term and grows only slowly in the longer term. New conventional oil fields take several years to bring into production and additional supply in the short term (within 1 year) can only come from either inventory, politically withheld supply (including, for example, Saudi Arabian spare capacity), shale oil production and infill drilling in conventional fields.Compared with demand elasticity studies, supply elasticity studies are rare. Caldara et al.22 compile six studies applying different methods and data and find short-term (within 1 year) supply elasticities in the range of 0-0.27. These estimates are based on historical data and do not necessarily reflect current or future oil supply. As a complement, we also rely on modelled forward-looking estimates of supply elasticity derived by Wachtmeister25 using a bottom-up modelling framework and Rystad UCube field-by-field data, as well as our own judgement of the current oil market outlook.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 129}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The main study area, Warren, encompasses the urban domain of the Red Run watershed located in southeast Michigan (Fig. 2a,b). This is a complex urban area with a substantial proportion of impervious surfaces. The land-use cover obtained from the National Land Cover Database 2019 (NLCD, https://www.mrlc.gov) indicates a predominant presence of developed areas with buildings, driveways, pavements and parking, with an impervious surface ratio reaching 94.48% (Supplementary  Fig. 18). The terrain in this region is relatively flat, with a northward slope adjacent Bear Creek. According to FEMA reports, some Warren  areas fall within the 100- and 500-year flood zones. To ensure a  realistic simulation, a substantial amount of digital and field observational data were collected to set up the model accurately. The overall simulation domain encompasses the entire Red Run watershed in which the Warren region is nested (Fig. 2a). This was done to ensure the modeling of spatial flood processes, such as surface inflows into the Warren area from other sub-basins and the simulation of flood waves in the Red Run River and its tributaries and their impact on the Warren area. High-resolution elevation data (0.6-m resolution)  were used to set up the overland flow model (Lidar Point Cloud data kindly provided by the USGS, https://apps.nationalmap.gov/ downloader/) (Supplementary Fig. 19a). Land-use and land-cover data with a 30-m resolution obtained from the NLCD were used to estimate roughness parameters for the model. Similarly, impervious surface data with a 30-m resolution, also derived from the NLCD, were used to estimate infiltration parameters. It is worth noting that other areas within the Red Run watershed also exhibited high impervious surface ratios, ranging mostly between 47% and 95%.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 130}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our approach to identification requires the assumption that not all areas that meet the CBRS delineation criteria were designated as part of the original system in 1982. This assumption is supported by the fact that additional areas have been added to the CBRS over the past 40 years, with the most recent addition proposed in December 202250. According to a 1988 Report to Congress51 and conversations with programme officers at the FWS, not all eligible areas were designated as part of the original system for two primary reasons. First, USGS quadrangles used in the inventory process did not show sufficient detail to identify all qualifying undeveloped coastal barrier areas. Second, the scientific definition of what qualifies as a 'coastal barrier' has evolved over time. We argue that both of these factors are plausibly exogenous to the housing market outcomes we analyse.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 131}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We use data on carbon pricing from the Carbon Pricing Dashboard of the World Bank. The dataset includes pricing policies at the national and  subnational level (Supplementary Table 2). We assign subnational  pricing schemes to the corresponding countries and focus on the first carbon pricing policy in every country. For a robustness test, we ignore subnational pricing policies. Furthermore, for another two robustness tests we keep only either carbon tax or ETS policies in the sample. For  the analysis of price levels, we combine this dataset with the World Carbon Pricing Database52. Data on GHG emissions are from a previous report53.  For the explanatory variables we use 9 different sources (Supplementary Table 2) for 21 raw variables (Supplementary Table 3). We use iterative  multiple imputation to fill missing values (see Methods). Descriptive  statistics of all covariates are shown in Supplementary Table 3. Our main sample covers 188 countries from 1988-2021 (Supplementary Fig. 1).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 132}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We conducted a content analysis of relevant policy documents, records from public meetings and public comments related to the rule-making  process. We used these data to complement and triangulate our  analysis from participant observation and interviews, and to confirm the elements of the regulations that were explicitly linked to equity and justice at different stages of the rule-making process. We gave special attention to justice controversies related to the implementation of BERDO and the role and positions of regulated parties, community advocates and other actors in proposing any specific regulations language or implementation decisions and strategies. This analysis included the final regulatory language adopted through the rule-making process, the minutes and materials from 15 public hearings of the Boston Air Pollution Control Commission, minutes and materials from 12 public hearings of the Review Board, minutes and materials from 11 CAG meetings, minutes and materials from 12 public meetings held by the City of Boston's Environment Department, 134 public comment letters received as part of the rule-making process, and nine documents that included city staff responses to public comment letters. A list of public meetings included in this analysis can be found in Supplementary Appendix C.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 133}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We calculated state-level time-varying measures of obstetric interventions, maternal demographics, and risk factors for \u201chigh-risk pregnancy\u201d among states' Black, Latina, and White childbearing populations. Our outcome measure was the proportion of births in state  in year j in which labor was induced, where i = Alabama,\u2026, Wyoming and j = 1990,\u2026,2017.5 Induction of labor is a characteristic of delivery that is comparable across the 1989 U.S. Standard Certificate of Live Birth and the 2003 U.S. Standard Certificate of Live Birth (Martin et al. 2007), and IOL coding in the NVSS is also comparable across U.S. states.6 As a control variable, we also created a measure of the cesarean delivery rate among first-birth singletons born to states' Black, Latina, and White women, calculated as the proportion of singleton first births in state i delivered by cesarean in year j.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 134}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Two units of analysis were used to examine the data. Data on respondents' role, interaction with interventions and general awareness of interventions were treated as data about the respondents, while data in response to survey question six onwards were treated as data about the intervention the respondent was asked to identify as the one with which they were most familiar. Selected choice data where respondents answered by selecting from a pre-determined set of options were analysed using basic descriptive statistics (frequency counts). These included questions to identify awareness of interventions, involvement in active intervention planning and deployment, the stage of development of the intervention respondents were most familiar with, the types of actors and organizations engaged in their development and the presence or absence of specific governance arrangements. Open-ended text responses were analysed using thematic content analysis102-104 to code data and thereby convert the qualitative data into quantitative data. To increase coding reliability105, first-pass coding frameworks were reviewed and tested by other members of the project team before finalizing and then undertaking the thematic analysis. Basic descriptive statistics (frequency counts) were then used to analyse the coded survey data by theme.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 135}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We use a stratified random sample of 1 km2 grid cells drawn from across countries with proportional allocation within states. To ensure a representative sample, countries are divided into two groups: those with more than 75,000 forested grid cells and those with fewer than 75,000 forested grid cells. For the first group, we randomly selected 10% of all grid cells. For the second group, we first determined the minimum random sample percentage according to Lohr18 and then proportionally sample this percentage of grid cells across states within countries. T he sample was limited to grid cells that had a minimum of 50% forest cover in 2010 and at least 25 ha of forest with canopy cover \u226560%. Brazilian forests in the Amazon biome are excluded from the analyses due to the existing monitoring system there. We study all countries that had access to the alerts before 2018 (Fig. 1a). The countries with fewer than 75,000 forested grid cells are: Burundi (70), Rwanda (638), Timor-Leste (3,862), Brunei (4,830), Uganda (8,813), Equatorial Guinea (25,352) and French Guiana (74,855). Using the same formula to sample the grid cells in the countries with more than 75,000 forested grid cells would lead to sampling less than 10%. To ensure representation within countries, sampling  for these locations is stratified at the second administrative level. Supplementary Table A11 presents the population of forested grid cells, sample sizes and corresponding sampling percentages. Sampling weights used in empirical estimations correspond to the inverse of the probability that the observation is included due to sampling design.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 136}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The circumstances that support this natural experiment arose in Jefferson County, which fully contains Louisville, a city that covers  842 km2 and had a population of 600,000 people in 2010. We hypothesized  that (1) coal-fired power plant emissions and subsequent population exposures dropped after the coal-fired power plant energy transitions and (2) the lower exposures resulting from energy transitions translated into fewer healthcare utilization events and symptoms. Our analyses used two health outcomes (acute asthma-related healthcare utilization and asthma symptoms) at two spatial scales (ZIP-code and individual level) and employed a measure of coal-fired power plant emission exposure.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 137}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    In this study, we explore the potential effects of fertility policy and its combination with retirement policy on the household carbon footprint. Specifically, there are three fertility policies: the two-child policy, the three-child policy and the assumed replacement-level policy. As for the retirement policy, we assume that the retirement age (as well as the threshold for older people in this study) is extended linearly from the Chinese current level (60 years for men and 55 years for women2) in 2020 to the age prevailing in developed countries (65 years for both men and women) in 2050, and remains constant afterwards (Supplementary Table 7)31. The fertility and retirement policies would affect the population and economy, thereby impacting the household consumption and carbon footprint in equation (16).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 138}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Here, we provide derivations of the model used in the analysis. We distinguish between the demand for crude oil for vehicle fuel in the EU, DEU, and the remaining oil demand DROW. Note that the rest of the world demand includes oil demand in the EU for uses other than vehicle fuel. Since we want to study the effects of taxes on vehicle fuel in the EU, we explicitly consider these and assume that the demand for oil for fuel in the EU depends on the price, including refinement, transportation and taxes. Let p denote the crude oil price, v the VAT rate and \u03c4 the per-unit tax on vehicle fuel in the EU. The costs for refinement and transportation could have one per-unit component, c, and one component proportional to the price, z. We thus have the fuel pricef=(1+v)((1+z)p+c+\u03c4) (10)and crude demand in the EU depends on this price and on income I, DEU(f, I). The rest of the world demand depends directly on the crude oil price DROW(p). In the baseline model, we focus on per-unit costs, corresponding to z = 0. In the Supplementary Information, we instead consider completely proportional costs, corresponding to c = 0.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 139}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We implement the global constraint on cumulative CO2 emissions via a global uniform carbon tax, which increases exponentially at a growth rate of 5% per year. In the first periods, the trajectory of the tax is smoothed out from the exponential path to avoid abrupt changes in the pricing profile. To mimic the existence of hard-to-abate sectors and emissions, the maximum rate of abatement via conventional mitigation MIUmax is capped at 0.975 for all countries, corresponding to 97.5% of baseline emissions and around 2 GtCO2 in 2100 globally. Non-CO2 gases are not priced and do not contribute to the global budget. To decrease the computational complexity of the problem and to avoid implicit transfers across regions via mitigation effort shifting, each region solves as an independent optimization and convergence is achieved by solving iteratively all regions. Nonetheless, the superimposed shape of the global carbon tax produces a de facto cooperative scenario even though each regional optimization problem is solved independently, in the sense that implicit cooperation is assumed in negotiating (and abiding to) the carbon tax level and growth across countries.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 140}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    GRID Alternatives tracks every point of contact with existing and potential clients (including referrals) in a Salesforce database. We analysed a de-identified version of data extracted from this database. Typically, once referred to the non-profit, individuals are contacted to determine whether their household meets the qualification criteria for subsidized solar (for example, they own their home, meet household income requirements, have a good roof and live in a qualifying area). Unfortunately for our study, some individuals were never screened; the dramatic increase in referred names from the reciprocity + simplification condition outpaced the non-profit's ability to process them as well as available funding for subsidized PV. Of the nominations that were not screened (94 during the first 17 weeks; 122 by 9 months), most came from the reciprocity + simplification condition (86.2% of non-screened at 17 weeks, 77.9% at 9 months; Supplementary Table 5). As this issue was only discovered at the start of the coronavirus pandemic, the non-profit was unable to recontact these individuals. This forced us to deviate from our analysis plan and proxy for quality by examining whether nominated individuals lived in areas that qualify for low-income solar subsidies through SASH and DAC-SASH. See Supplementary Note 1.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 141}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Those communities that we focus on are typically exposed to extremely hot days and cold nights. Supplementary Table 13 shows the breakdown of key temperature statistics by climate zone for these communities. Figure 1 presents maps produced by the Australian BOM showing how temperature differs across both Australia and the NT72. Differences in temperature indicators vary across climate zones (shown in Fig. 1a-c). Central Australia experiences prolonged hot daytime temperatures in summer and cold (below zero) nights in winter. For example, the hottest day (46 \u00b0C) and coldest night (-4 \u00b0C) in our dataset both occurred in the southern-most 'hot persistently dry grassland climate zone'. Northern regions of the NT experience the southern extent of the tropical monsoon, which brings seasonal cyclonic activity and afternoon storms. Average temperatures decrease north to south. The highest maximum temperature (lowest minimum temperature) increases (decreases) as you move from the north to south (Fig. 1b,c and Supplementary Table 13). The regressions were run using daily average temperatures.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 142}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Each project has a unique reference number that stays the same across all database snapshots, as confirmed by the IEA in personal correspondence. This enabled us to track the development of project announcements over time (see Fig. 3 for projects announced for 2023, Supplementary Fig. 5 for projects announced for 2022 and Supplementary Fig. 6 for projects announced for 2024). Supplementary Figs. 7-10 also show the 2023 project tracking for those regions that have at least ten trackable project entries. We accounted for changing capacity of projects between two database snapshots by adding dummy projects, which are, however, not explicitly shown in the Sankey diagrams for simplicity. The reported rates of disappearance, delay and success (Fig. 3b-d and Supplementary Fig. 5b, c) only refer to projects announced in 2021, 2022 and 2023, respectively.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 143}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our research methodology is informed by the principles underpinning ethical Australian Indigenous research outlined in the Australian Institute of Aboriginal and Torres Strait Islander Studies Code of Ethics for Aboriginal and Torres Strait Islander Research71, and our research team is committed to the principles of Indigenous self-determination, Indigenous leadership, impact and value, sustainability and accountability. V.N.D. is senior Aboriginal researcher at Tangentyere Research Hub in Mparntwe (Alice Springs) and a visiting Indigenous fellow at the Australian National University (ANU) Centre for Aboriginal Economic Policy Research. M.K. is senior policy manager at Tangentyere Research Hub and a visiting fellow at the ANU's Centre for Aboriginal Economic Policy Research.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 144}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We now describe our procedure for identifying plausible control areas: areas that could have been selected for CBRS designation in 1982 based on the selection criteria, but were not. CBRS boundaries do not follow traditional administrative boundaries; they were hand drawn to follow geomorphic and development features44. Our first step is to trace out potential counterfactual areas using an automated procedure that closely resembles this process. Importantly, we can observe close proxies for the information the planners had available at the time of designation\u2014aerial photographs and topographic maps (Extended Data Fig. 2). We begin with 300 m resolution gridded data on historical land cover, development levels, elevation and distance to coast. Each cell of the raster represents a distinct observation that will be grouped into a region. We only consider grid cells within 2 km of the coast. We exclude any cell that is 100% water, within a CBRS unit (including both original units designated in 1982 and all units designated since then) or an otherwise protected area, and all grid cells within 2 km of a CBRS unit (to avoid selecting control areas that may be 'treated' by spillover effects of CBRS units).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 145}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    On the basis of the literature evaluations and feedback from the stakeholder survey, we compiled a comprehensive list of measures that were considered to have substantial impact on reducing demand-side emissions, while also being regarded feasible. We classified these measures into three different intervention strategies, based on a slightly adapted version of the ASI (Avoid-Shift-Improve) framework3. Categorizing policy measures in the ASI framework can be ambiguous in some cases. For example, stimulating adoption of heat pumps both improves the building technical systems and induces a shift from higher-carbon fuels to electrification for space heating. Because we aimed to explore which type of policy interventions are most effective, we needed a cleaner separation between the mitigation options and we use a more distinct separation between the demand-side measures. Table 1 summarizes the key assumptions for the three intervention strategies.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 146}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We utilized the Prescription Drug Abuse Policy System for a comprehensive listing of policy passage in each U.S. state between 2000 and 2016. We then created a state-year data set of the presence of policies across the observation period. Our central variable of interest is presence of a state-level PDMP (coding described in the following). We also considered alternative specifications via variables for whether prescribers/dispensers have access to the PDMP and whether prescribers/dispensers are required to check the PDMP when writing/filling a prescription. To account for other policies that may affect overdose rates, we included covariates for naloxone access expanded beyond medical settings, Good Samaritan laws absolving criminal/civil liability in reporting an overdose, pain clinic restrictions, and medical marijuana laws (not passed because of the overdose crisis but an important policy covariate given their pertinence to managing pain)\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 147}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    This criterion looks at alignment between adaptation cycle components. Policies need to establish clear linkages between climate risk and impact assessments, planning of goals and objectives, actions to implement, and MEL, to facilitate context-fit tracking and meaningful insights on progress21,30. Intentional linkages maximize effectiveness of plans in reducing risks and vulnerabilities28. Our assessment of consistency was pragmatic and did not examine the extent to which sets of actions sufficiently address risks. A document was considered fully consistent if it provided evidence of intentional linkages across all four components of the adaptation cycle. For instance, actions to switch to drought-resistant crops or strengthen early warning systems for hydroclimatic risks in coastal areas indicate linkages between assessment and planning (Supplementary Table 3). While such an approach is inherently subjective, it provides a practical, preliminary approximation of how policies can deliver meaningful information for tracking.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 148}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Here we formulated a multiple-agent variant of a two-stage stochastic program for capacity expansion. In the first stage, risk-averse investment and financial trading decisions are made by a number of agents. Spot market prices are determined through a perfectly competitive dispatch over time blocks, t2T I ,  performed by the system operator in the second stage. The ultimate source of all generator revenue in the model is energy sales; financial contracts settle based on the prices realized in the second stage. Instead of writing the optimality conditions for each of the subproblems and reformulating as a complementarity problem9,41,42, we anticipate the algorithm that we describe later in this section and focus on the problems solved by each agent. Our modelling framework builds most directly on the approaches of de Maere d'Aertrycke and co-workers41,]42, which describe a risk-averse capacity equilibrium with incomplete markets. We make two modifications of note, which we describe in detail after introducing the model. Incomplete trading has significant ramifications, both computationally and conceptually. The computational issue is that, instead of a comparatively simple optimization problem, the problem is formulated using a construct called a multiple optimization problem with equilibrium constraints43. Although modest-sized instances can be solved by the PATH solver44, numerical tests on larger instances can fail to converge. To help address this issue, we proposed a heuristic decomposition algorithm similar in spirit to that of H\u00f6schle et al.45, which allows the identification of equilibria through a series of convex quadratic programs. Although the test systems used in this article are kept simple, this decomposition approach allows an easier extension to a richer set of technologies and risks. The conceptual concern is that the uniqueness of the equilibrium solutions cannot, in general, be guaranteed. We revisit this topic after introducing the algorithm. The optimization models are implemented in AMPL46 and solved using CPLEX47 \n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 149}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We model the impacts of three policies\u2014setbacks, an excise tax and a carbon tax\u2014on California's oil sector. A setback policy prohibits oil (and gas) extraction within a specified distance from sensitive sites including occupied dwellings, schools, healthcare facilities and playgrounds. We model two setback scenarios: (1) setbacks that apply to new wells only (main results) and (2) setbacks that apply to new and existing wells or all wells. We model setbacks on new wells by proportionally reducing field-level future new well entry based on the relative field area covered by a given setback buffer. For existing wells, setbacks are implemented in our model by removing those within the setback distance from future production. We consider setback distances of 1,000 feet, 2,500 feet and 1 mile. We assume only vertical drilling in the setback analysis. Horizontal and directional drilling from pads outside of the setback distance could access additional sub-surface oil resources within the setback distance, reducing our estimates of the health and equity benefits of setbacks, especially for shorter setback distances44. However, the costs and extent of adoption of horizontal drilling are uncertain for California and thus are not included in this study. The excise-tax policy imposes a tax on each barrel of crude oil extracted. In our projection period, we apply a constant tax rate to the oil price each year. This is consistent with historical proposals for excise taxes on California oil extraction45. The carbon-tax policy imposes a tax on the GHG emissions from the oil-extraction site. We consider only direct GHG emissions, excluding methane emissions due to a lack of reliable oil-field-specific data. All carbon-tax trajectories increase at an annual rate of 7%, the sum of a 5% real growth rate and 2% inflation rate per year (ref. 46). We determine the excise-tax rates applied to the oil price and carbon taxes that result in the following 2045 statewide GHG emissions targets using an optimization function: (1) 2045 statewide GHG emissions associated with the three setback distances (Supplementary Table 4) and (2) a 90% reduction in statewide GHG emissions compared with 2019. The excise and carbon taxes are shown in Supplementary Figs. 15 and 16 and are inputs to the oil-extraction model and affect future well entry and exit. Summplementary Note 17 provides more details.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 150}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We assume that gross consumption is distributed across population quintiles according to a baseline distribution, yielding gross consumptions for each quintile. Under the no recycling scenario, final consumption of each quintile is computed by subtracting climate damages and mitigation costs from gross consumption according to distributions that reflect different exposures and vulnerabilities of consumption groups to these impacts. Under the recycling scenario, carbon taxes are raised according to the same distribution as mitigation costs and redistributed as equal per capita payments within regions. The baseline distribution is given by quintile weights, qijt , that denote the ratio between quintile consumption and average consumption. If for quintile j in region i and period t, qijt > 1, its consumption is greater than average regional consumption in that period; if qijt < 1, its consumption is less than the average. Since the five quintiles comprise equal proportions of the population, \u2211 j qijt=5 in all regions and periods. In the base implementation these quintile weights are fixed across time and estimated to the current distribution of consumption in the region by aggregating country level distributional data from the World Income Inequality Database58 to regional distributions. The aggregation is described in detail in Section 6 of the Supplementary Information.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 151}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To investigate voters' policy preferences, we conducted a choice experiment. Choice experiments were developed in marketing research to investigate the importance of different product design features in determining purchasing preferences. The idea is to put respondents in a hypothetical yet realistic choice situation in which they are confronted with bundles of relevant product attributes. By observing stated preferences with regard to the presented alternatives, it is possible to examine the relevance of certain product attributes and their characteristics to individual choices. Political scientists have adopted the method to gauge citizens' preferences with regard to different policy proposals or scenarios26,49. Analytically, the design features of a policy are similar to product attributes, which is why the method provides a powerful approach to simultaneously estimate the individual effects of several attributes of a policy proposal on voter preferences50. Choice experiments require decision-makers to make trade-offs between different policy attributes when evaluating various multidimensional alternatives. As a consequence, they can mitigate the problem of social desirability bias in public opinion research on environmental matters26. In our case, using choice experiments may reduce the likelihood of overestimating voters' appetite for an ambitious phase-out of coal.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 152}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The first step of the econometric methodology identifies a cointegrating relation for the real price of oil from an unrestricted model, which is given by: Pricet\u00bcf UtilTRCt;UtilTRC2 t ;UtilTRC3 t ;UtilOPECt;UtilOPEC2 t ; UtilOPEC3 t ;Dayst;UtilReft \u00f04\u00de for which the variables have been defined previously. We identify a final version of equation (4) by estimating versions that specify all possible combinations of utilization rates by the TRC and OPEC (Supplementary Note 1) and evaluating each model against three criteria: do the variables cointegrate, do the variables have a statistically measurable relation with oil prices and do oil prices error correct to disequilibrium in the cointegrating relation? We evaluate cointegration by estimating each possible specification using OLS and testing the residual for a unit root with four statistics (PT, DFGLS, QT and DFGLSu)56. Statistics that reject the null hypothesis indicate that the residual does not contain a unit root, which indicates that the variables cointegrate and therefore represent a long-run cointegrating relation for price. The long-run relation between Price and the proxies for the balance between supply and demand are estimated using DOLS57. Lags and leads for the first differences of the independent variables are chosen using the Bayesian information criterion58. We test the null hypothesis that independent variable i has no statistically measurable relation with Price (\u03b2i = 0) with a t-test that is calculated with a standard error, which is robust to the presence of autocorrelation and heteroscedasticity in the regression residual59. Rejecting the null hypothesis indicates that independent variable i has a statistically measurable relation  with Price.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 153}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our energy performance data (total energy use and EUI) and audit data were collected by the NYC Department of Finance and the Department of Buildings pursuant to LL84 and LL87. Data were provided by the NYC Mayor's Office of Sustainability subsequent to a data sharing request. The LL84 dataset includes all covered buildings, which are defined as buildings with greater than 50,000 ft2 of gross floor area, that submitted energy use data in calendar years 2011 through 2016. EUI is defined as the total annual energy consumption divided by the gross floor area of the building, and we utilized weather-normalized site EUI to capture the direct consumption reported through utility bills adjusted for the total number of heating degree days and cooling degree days in a given year57. In addition to the total energy use and EUI values, the dataset contains buildingspecific features, which include physical (age, gross floor area and so on) and operational (occupancy density, weekly operating hours, conditioned spaces and soon) characteristics.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 154}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    For models in which the proxies for market fundamentals cointegrate with price, have a statistically measurable relation with price and oil prices error correct to disequilibrium in the cointegrating relation, we identify price regimes using an indicator saturation technique that is implemented in the R package gets (refs. 61,62). We 'fix' the independent variables used in the DOLS estimate (along with the lags and leads of the first differences), use a P = 0.01 significance level and allow gets to choose from a full set of impulses and/or steps. Impulses are a one-quarter change in the equilibrium price for crude oil relative to that simulated by the proxies for market fundamentals in the cointegrating relation, while steps are changes that persist for two or more consecutive quarters. Impulses and steps are evaluated iteratively for every possible quarter. The method used to calculate the statistical significance of impulses and steps is summarized in Supplementary Note 2.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 155}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Before deploying wave 4, we estimated the objective rebate received by each survey respondent from Ontario and Saskatchewan, using their province of residence, reported marital status (including common law), number of children residing with them as reported in wave 3 and whether their NaTuRE ClImaTE CHaNgE residence is rural (for example, outside a census metropolitan area (CMA)) and thus eligible for an additional rebate. These factors completely determine dividend levels within the current Canadian policy, which we calculated using Revenue Canada income tax worksheets. Note that dividend levels are not a function of income in Canada. For CMA measurements, we determine the respondent's place of residence using the Postal Code Conversion File provided by Statistics Canada, which gives us a range of geographic identifying variables (such as residence in a CMA and electoral district) for each of the self-reported postal codes collected in our survey. We summarize the rebate calculation process for 2019 in Supplementary Section 23. As part of an embedded survey experiment in wave 4,  we randomly assigned half the respondents to receive a filled-out tax form that showed them their own household rebate amount (Supplementary Section 12). Details about question wording in our survey instrument are presented in Supplementary Section 24. All respondents were given the option of responding in either English (n = 752) or French (n = 147).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 156}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We first describe the selection process for CBRS designations, as our empirical approach relies on replicating it. The CBRS designation process is described in detail in the 1982 Federal Register and in refs. 42,43, where the US Fish & Wildlife Service (FWS) establishes a set of 'definitions and delineation criteria'. CBRS designations were then based upon the application of these criteria to on-the-ground situations. The first criteria for CBRS designations is that the land should be a 'coastal barrier', a class of low coastal land forms that protect landward areas from tidal, wave or wind energies. For the purposes of CBRS designations, the definition of coastal barriers also includes all associated aquatic habitats such as adjacent wetlands, marshes, estuaries, inlets and nearshore waters. In addition to meeting this geological definition, the CBRS requires coastal barriers to be 'undeveloped' in order to be included in the system. Specifically, the delineation criteria state that an area should be considered \u201conly if there are few manmade structures on the barrier or any portion thereof and these structures and man's activities on the barrier do not significantly impede geomorphic and ecological processes\u201d42.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 157}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Electronic copies of transcriptions and field notes were manually coded using NVivo qualitative software and summary spreadsheets. Analysis of themes reported here was inductive: We had no a priori expectation about what children's health lifestyles consisted of, how health or health behaviors were defined, or how they would vary. We analyzed observational field notes together with parent interviews to compare personal accounts to observed behaviors, allowing themes to arise organically and coding for some predetermined themes. People's public and private accounts and behaviors are often inconsistent in sociologically meaningful ways (Swidler 2001). Because the communities' health lifestyles were similar even though distribution and degree varied, we combined the communities here. We viewed the interviews and focus groups as opportunities for participants to actively construct narratives (Holstein and Gubrium 1995). Through narratives situated in specific social contexts, people construct identities, justify actions, and manage others' impressions (Swidler 2001). Narratives, which shed light on norms, individual and group identities, and inequalities, turned out to be an important aspect of children's health lifestyles. Our goal was not to adjudicate whether parenting, specific health lifestyles, or their consequences are good or bad.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 158}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Annual data on life expectancy by state were obtained from the United States Mortality Database (https://usa.mortality.org/). Life expectancy is an ideal indicator of overall population health because it reflects age-specific mortality rates spanning all ages for a particular year. Our key indicator of income inequality was the income share of the top 10% of earners based off pretax gross income reported to the Internal Revenue Service. These data were obtained from the U.S. State-Level Income Inequality Database, developed by Mark Frank (2015) and constructed from individual tax filing data available from the Internal Revenue Service. From the same source, we also obtained alternative measure of income inequality to use in supplemental analyses. These measures included the share of the top .1%, 1%, and 5% of income earners and the Gini index. The main source of data on state policies came from Grumbach (2018). These measures, shown in Table 1, contained 135 policies spanning 16 domains: abortion, campaign finance, civil rights and liberties, criminal justice, education, environment, gun control, health and welfare, housing and transportation, immigration, private sector labor, public sector labor, LGBT rights, marijuana, taxes, and voting. Evidence on how these policy domains are plausibly linked to life expectancy are described elsewhere (Kemp, Grumbach, and Montez 2022). For each state, the data contained a score for each domain annually from 2000 through 2014.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 159}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We measured individual tendency to discount future events and the preference for consumption smoothing using the convex time budget method28,29. The allocation of payments xt and xt+k between period t and t + k was considered. The utility function of an individual was defined as: \u00f0 Uxt;xt\u00fek \u00de\u00bc xalpha t \u00fe\u03b2\u03b4kxalpha t\u00fek if t \u00bc 0 xalpha t \u00fe \u03b4kxalpha t\u00fek if t>0 where alpha measures consumption smoothing as the utility function curvature, \u03b4 denotes long-run time discounting, and \u03b2 captures present bias. We estimated these parameters using the choices of respondents in a convex time budget task. In this task, respondents were asked to select a bundle of payments that would be received at time t and t + k, where each choice comprised the cases in which the full payment occurred at time t and t + k and also included four convex combinations. For example, a choice task might ask respondents to choose between a combination of US$19 today and $0 in 5 weeks, a combination of $0 today and $20 in 5 weeks, as well as the following four convex combinations of these two: $15.20 today and $4.00 in 5 weeks, $11.40 today and $8.00 in 5 weeks, $7.60 today and $12.00 in 5 weeks, and $3.80 today and $16.00 in 5 weeks.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 160}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    This criterion describes inclusion of key elements of the adaptation cycle, which describe the 'why', 'what', 'how' and 'so what' of adaptation. This approach builds on an existing framework to track adaptation among governments15, which suggests that a comprehensive understanding of adaptation progress rests on an assessment of the vulnerability context, goals, actions and results. In our assessment, policies with adequate coverage include information on six  core elements mapped to the adaptation cycle (Supplementary Table 2). Hazards, systems at risk, goals, objectives and actions provide context to tracking and inform the development of adequate and meaningful indicators30. Together, these six elements deliver a baseline understanding of intentions for adaptation.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 161}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Following the IPCC and State of CDR reports, we defined CDR as \u201cHuman activities capturing CO2 from the atmosphere and storing it durably in geological, land or ocean reservoirs, or in products. This includes human enhancement of natural removal processes, but excludes natural uptake not caused directly by human activities.\u201d1,2 Important characteristics of this definition are its unambiguous inclusion of both conventional land-based sinks and emerging CDR methods, as well as requirements for durability and direct human intervention19. A wide array of CDR technologies have been developed, tested or are in practice today60. In this Analysis, we follow ref. 2 and categorize afforestation, reforestation, forest management, soil carbon sequestration, wetland restoration and durable harvested wood products as 'conventional CDR on land'. 'Novel CDR' comprises all other CDR methods,  such as biochar as well as those that store carbon in the lithosphere including direct air carbon capture and storage (DACCS), bioenergy carbon capture and storage (BECCS) and enhanced weathering.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 162}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    For this paper, we capitalize on the OMCs' robust information technology platform, which electronically stores enrolment and sales records for all registered LPG consumers. We use this source to extract two datasets at different resolutions. For the first, we use a national database of LPG purchase by PMUY beneficiaries aggregated at the state level. These data were made available by a senior official from the Ministry of Petroleum and Natural Gas, Government of India. It contains data on 30 million PMUY beneficiaries, aggregated by state, who have completed at least 1 year as LPG consumers (based on their date of enrolment). For regression analysis to explain the state-wise variation in LPG consumption, refer to Supplementary Note 9 and Supplementary Fig. 12. For further details of the regression analyses and validity checks of the underlying assumptions for linear models, see Supplementary Code 1 hosted on Figshare45. The second dataset comprises sub-district level data gathered from three Indian Oil Corporation Ltd (IOCL) LPG distributors in Koppal district of Karnataka state. These were conveniently located near another ongoing project site. The three distributors D1, D2 and D3 serve 25,000 domestic consumers from around 120 villages across four taluks. While the data gathered include both commercial and domestic consumers, we analysed only data for domestic consumers in this research.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 163}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our selection of IAM scenarios drew from the latest IPCC AR6 vetted  scenario database20. We used the C1 and C3 scenario categories, which together are referred to as 'below 2 \u00b0C scenarios' in the main manuscript. These scenarios could be considered as those most relevant to, but not necessarily all consistent with, the Paris Agreement temperature goal. We used the scenario re-analysis provided in ref. 21 that splits emissions and removals in the land-use sector. Their analysis was conducted by running the OSCAR bookkeeping model using variables reported in the AR6 scenario database, including forest land area, cropland area and forestry activity, to evaluate the direct anthropogenic removals on managed land. These scenario projections followed and extended the experimental setup used for the 2021 Global Carbon Budget68.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 164}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We modeled U.S. states' IOL rates between 1990 and 2017 separately for Black, Latina, and White women. We fit generalized linear mixed models to estimate the year-specific state-level rates as outcomes of a fixed effect linear slope, a random intercept, a random slope, and state-specific residual variance: Yij=\u03c00i+\u03c01iYearij-1990 /5+\u03b5ij \u03c00i=gamma00+\u03bc0i \u03c01i=gamma10+\u03bc1i. (1) Assuming \u03bc0i \u03bc1i N 0 0 , sigma0 2 sigma01 sigma10 sigma1 2 and \u03b5ij ~N0,sigma\u03b5 2 where Yij is the IOL rate for state i in year j, where i= Alabama,\u2026,Wyoming and j=1990,\u2026,2017; gamma00 is the average IOL rate among U.S. states in year 1990; \u00b50i is the estimated deviation from gamma00 for state I in 1990; gamma10 is the average five-year change in IOL rate between 1990 and 2017; \u00b51i is the estimated deviation from gamma10 for state i; and \u03b5ij is the Level 1 residual variance for state i in year j. We divided the slope by 5 for interpretation reasons (i.e., the estimated coefficient indicates the expected change in states' IOL rates over a five-year time span), and increasing the slope size improves estimates of the variance component of \u00b51i , sigma1 2 (Singer and Willett 2003).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 165}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used a combination of government documents, oil and gas industry reporting, and media reports to extend the original 2000-2015 data to December 2023 for our sample. Data are missing for 173 of the 8,568 country-months owing to periods of political disruption for Myanmar and Venezuela. The countries in our sample are located in different regions\u2014Latin America, the Middle East, North Africa, Central Asia, Sub-Saharan Africa and Southeast Asia\u2014yet share two important characteristics: they are exporters of oil or fossil gas; and they tend to set fuel prices by government fiat, protecting them from global price fluctuations. The use of fixed gasoline prices creates a link between the global oil price and the size of the subsidy: when global prices rise, so do the benefits accruing to local consumers who continue to enjoy the fixed price and, hence, are receiving a larger per-unit subsidy.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 166}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The fertility and retirement policies affect the population in terms of size and structure, respectively. In particular, we project the population under different fertility policies with different fertility rates following the cohort-component method. As for the retirement policy, we use retirement age as the threshold to classify older people, such that the retirement policy affects the population age structure31.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 167}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The GLOFRIS flood risk model follows a commonly applied hazardexposure-vulnerability model25,26. Coastal and fluvial inundation maps were combined with land use to simulate the (future) exposure of assets and their values in flood zones. Depth-damage curves were used to combine hazard and exposure data to simulate flood risk (expected annual damage, EAD, in US$ per yr) for each individual grid cell and county. Floods can stochastically occur every year in each county on the basis of their return period. See also Extended Data Fig. 1a and Supplementary Information.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 168}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Most countries tax the consumption of fossil fuels rather than subsidize it. Among those that subsidize, some target their subsidies towards low-income, vulnerable populations and use them for relatively brief periods; others subsidize most or all of their citizens over many years. Our study is concerned with the latter group of countries, which are typically the focus of international efforts to reduce fossil fuel subsidies. We follow convention and define a subsidy as the difference between the price paid by consumers and the cost of bringing the fuel to market14. To measure the size of these subsidies, we use the price gap method, which compares the observed retail price of a fuel in each country with a global benchmark price, which represents the supply cost. Anytime the retail price falls below the benchmark price (for example, the cost of supplying the fuel), it denotes a subsidy for that period. To identify the countries that were net subsidizers in the pre Paris era, we use the ref. 15 dataset of monthly gasoline taxes and subsidies, which covers 157 countries. We include in the sample all countries whose median gasoline price for the 2003-2015 period was below the median benchmark for the same period, meaning they were net subsidizers during this initial period. This yields 22 countries, one of which (Yemen) we drop due to missing data in the period after its civil war began.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 169}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The online survey-questionnaire was launched on 31 October 2022 and remained open until 15 March 2023. Three hundred and thirty-two responses met the criteria for level of question completion and were retained for analysis. These responses included those undertaken in five non-English languages\u2014Chinese, Japanese, French, Portuguese and Spanish\u2014which accounted for 18% of the final sample. These responses were translated into English by native speakers with marine expertise before analysis. Survey data were not treated to any weighting to adjust for the expected population because the survey population was an emerging specialist group, and population characteristics were not established. Response rates to the survey by sub-group are therefore not reported. Representativeness of the survey data was therefore subject to sample bias although recruitment methods were adjusted to target non-English speakers in five other languages and practitioners in non-scientific networks. A degree of sample bias was accepted as an expected limitation of the study due to the nature of the emerging group being surveyed and the online survey-questionnaire instrument used101. No identifying data were collected from respondents although in some cases participants provided personal identifying data in response to open-text questions.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 170}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We translate oil production (crude oil, condensate and natural gas liquids) in barrels per day to a corresponding volume of refined products. We make the simplifying assumption that one barrel of oil yields 170 l of products and fuels that can be sold to consumers. In the base case, the variable production cost of these fuels is assumed to correspond directly to the crude oil price (that is, the variable fuel production cost is the global oil price per barrel (Brent; in US$ per barrel) measured in Euros per litre of fuel product (p)). The retail fuel price (consumer price) is then the variable fuel production cost (oil price, p) plus the other, fixed, production costs, c (refining, transport, margins and so on), plus the fuel tax, \u03c4, then VAT is applied to all of these. In the sensitivity analysis (see Supplementary Note 3), we explore other variable production costs (z) and discuss which case is more likely. Our base case c of \u20ac0.45 l-1 is derived backwards from a consumer price of \u20ac1.9 l-1. c thus includes the current refinery margins (the value difference between crude oil and refined products), which vary in time and are currently at historically high levels.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 171}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We conducted focus groups with prenatal genetic counselors and ob-gyns employed in a variety of Ohio hospital settings (e.g., private, public, academic, religious). Focus groups are a useful method for exploratory research that enables respondents with similar characteristics, such as profession, to engage in conversation. Participants who were unable to attend focus groups shared their experiences in individual, semistructured interviews. The University of Cincinnati's Institutional Review Board approved this study. Participants were recruited through professional society memberships and listservs, advocacy groups, university-affiliated hospitals, and snowball sampling. Participants were eligible if they were ob-gyns or genetic counselors who worked in Ohio for at least six months between 2010 and 2020. We excluded providers working in dedicated abortion clinics because the impact of abortion regulations on those who work in abortion clinics has been well documented. Less understood are the implications of these laws for general obstetricgynecological practice and for abortion-adjacent health care providers\u2014such as genetic counselors\u2014 who work in the same state regulatory context. Genetic counselors counsel patients on their reproductive options, including abortion, prior to prenatal testing and following prenatal diagnosis. Ob-gyns interact with patients who need a range of reproductive health care, such as abortion, contraception, and management of miscarriage and ectopic pregnancy.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 172}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We took a new wind energy development project as the starting point of the analysis. From this lens, we considered all the turbines that need to be dismantled to enable the undertaking of the new project (as a conditional requirement). We used the term dismantling, but, in principle, our approach can capture both the complete dismantling of turbines (also referred to as full repowering4), and the installation of new equipment (for example, drivetrain and rotor) on an existing tower and/or foundation (also referred to as partial repowering4). We emphasize that the analysis must include the dismantling of existing turbines not only at the location of the new project undertaking (on-site), but also those located elsewhere (off-site). Furthermore, existing turbines may be dismantled years before the new turbines are installed. Therefore, repowering must reflect a combined action of dismantling existing turbines and establishing new turbines, regardless of spatial or temporal proximity. We thus investigated the conditional relationship between capacity reduction and capacity addition. This enabled us to reveal notable differences between repowering projects (comprising both commissioning new turbines and dismantling existing turbines) and greenfield projects (only comprising the commissioning of new turbines) for several key indicators, such as project size and lifetime.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 173}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We multiplied a single general linear trend (Hg/OC ratio: 3.95 \u03bcg g-1) between OC and Hg in all coastal sediments generated from our regional observational data (Fig. 1c) by the Blue C stock in different Blue C ecosystems compiled by others to roughly estimate the Hg stock in the top metre of sediment in global coastal environments (Blue Hg stock; Fig. 1d). The van Bemmelen factor (LOI/OC = 1.724) is used to convert sediment LOI to OC content. The Blue C stock in global mangrove forests (mean = 5,150 Tg OC, range = 1,900-8,400 Tg OC), seagrass meadows (mean = 11,366 Tg OC, range = 1,732-21,000 Tg OC) and tidal marshes (mean = 1,106 Tg OC, range = 862-1,350 Tg OC) was obtained from ref. 3 and tidal flats (900 Tg OC) from ref. 4. We applied the identical method to estimate the Blue Hg fluxes. Since the huge uncertainties of current Blue C stocks and fluxes dominate the uncertainties of Blue Hg stock and flux estimates in the present study, we did not consider the error propagation of sediment LOI and Hg determination and the regression coefficient of OC and Hg in the calculation.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 174}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    My analysis comprised two stages: starting with applying multichannel sequence analysis (MCSA) and cluster analysis to build simultaneous career and family formation trajectories and followed by logistic regression models to examine the likelihood of being at high risk of depression across these trajectories. MCSA, an advanced form of sequence analysis (MacIndoe and Abbott 2011), facilitates the comparison of life trajectories in multiple domains by using operations such as insertion/deletion and state substitution for optimal matching. This led to various work-family trajectories, with costs based on the inverse of state probabilities and a constant insertion/deletion cost.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 175}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We test observed (unconditional) differences for the hypotheses described in the main text. We use Wilcoxon rank-sum tests to test hypotheses for household incomes and Pearson \u03c72 tests for the categorical variables (housing tenure, housing type, race). We compare medians because household income levels are not normally distributed. We make two adjustments to ensure independence between the comparison groups. First, we estimate comparative statistics within states to ensure that the community and rooftop solar data are pulled from the same geographic subsamples. Second, we restrict the rooftop solar adopter data to systems installed in 2022 to account for the fact that our community solar data reflect samples of customers enroled in community solar in 2022 or 2023. That temporal misalignment matters because rooftop solar adoption has become more demographically equitable over time5. Both restrictions are reflected in the sample sizes reported in Table 1.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 176}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    First, differences by family social class in the marginal effects of diagnosis were estimated overall and then separately by whether or not the child subsequently received medication following diagnosis. In the latter analyses, diagnosed children were further classified as those who \u201cadditionally receive medication\u201d and those who \u201cdo not receive medication,\u201d both relative to undiagnosed children. This moderation analysis (first by family social class and then also by medication status) occurred after CEM but before PSM (Stuart et al. 2009). To guard against reverse-causality issues, sensitivity analyses relied on medication receipt reported only in third grade; resulting estimates remained substantively unchanged. Baseline models pooling across social class are shown in Appendix Table A.1. The CEM package in Stata 14 was used to independently and ex ante ensure that diagnosed and undiagnosed children were \u201cexact matches\u201d on three characteristics on which there are well- established differences in diagnosis and future behaviors: (1) family social class (3 groups); (2) quartile of pre-diagnosis behavioral problems based on parent- and teacher-rated subscales for inattentive or hyperactive/impulsive behavioral type (16 groups); and (3) child sex (2 groups). The continuous variables for social class and pre-diagnosis ADHD-related behaviors were first temporarily \u201ccoarsened\u201d into the above categories so that matching occurred within the 96 broad groups above (3 x 16 x 2 = 96). All 380 diagnosed children were successfully matched to otherwise comparable undiagnosed children. By contrast, 340 (.5% of) undiagnosed children were pruned for reasons of achieving balance described in the Online Appendix.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 177}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The NICE model extends RICE by disaggregating regional consumption into five socioeconomic groups with consumption levels reflecting the current distribution of consumption within the regions58. So as not to affect any of the aggregate economic variables (investment, capital, output and so on), this is done by splitting average regional consumption into five units (or quintiles) after aggregate savings have been determined. The background consumption distribution and the distributions of damage and mitigation cost are determined in the way described below. We denote regions by index i, quintiles by j and periods by t. Quantities without a j index are regional aggregates and are identical to the quantities in the more aggregated RICE model. Net output Yit is given by Yit=1-\u03bbit 1+Dit Qit (1) where Qit denotes gross output, \u03bbit mitigation cost (opportunity costs of reducing CO2 emissions as a share of GDP) and Dit climate damages. The basic trade-off of the RICE model\u2014mitigation costs in the present for the reduction of climate damages in the future\u2014is embodied in this equation. As mentioned above, in each period the regional mitigation costs are chosen so that they are consistent with a globally uniform carbon price, which is implemented as a local tax, taxt , in each region.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 178}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Country long-term strategies were downloaded from the UNFCCC and were qualitatively coded in a spreadsheet by two independent coders, a research assistant and a member of the research team, for the following information: (1) Type of target (for example, carbon neutrality, net zero or other) (2) Coverage of target (GHGs or CO2 ) (3) Year of net zero, for countries with net-zero or carbon-neutral targets (4) Whether there is a definition of residual emissions or hard-to- abate/remaining emissions and, if so, how it is introduced (5) Whether there is a quantitative projection of residual emissions at net zero and, if so, what the amount is (6) Sectoral breakdowns of residual emissions (7) The source and process of generating the projections (which approaches were used; whether they appeared to be top-down or bottom-up; which particular models were used to generate them) (8) Mentions of public or stakeholder consultation or engagement In a few cases, other government documents or sources were also used for reference, including technical annexes for government strategies. Percentages of current country emissions were derived from the World Resources Institute's Climate Watch platform at https://www. climatewatchdata.org/ (ref. 1). Current-year emissions were derived from the 2019 emissions listed in UNFCCC inventories for total GHG emissions without LULUCF, at https://unfccc.int/process-and-meetings/transparency-and-reporting/ greenhouse-gas-data/ghg-data-unfccc/ghg-data-from-unfccc. Recent and current LULUCF data are from (ref. 35). The coded data was used to generate the tables and figures  in the Article. The analysis is straightforward; the work was simply in extracting the amounts of residual emissions and sectoral breakdowns because these are not presented in a standard form across  the documents, and in some cases they appear in charts but are  not well explicated in the main text of the reports.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 179}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Interviews and focus groups were audiorecorded. Focus groups were 90 minutes; individual interviews lasted 45 to 60 minutes. The recordings were transcribed and deidentified, including provision of pseudonyms for participants. At least two members of the research team thematically coded each transcript using ATLAS.ti, a qualitative analysis software. Coders met regularly to discuss themes and resolve discrepancies. Analysis consisted of an iterative process of thematic categorization, consultation with relevant literature, discussion of themes, and revisiting the data and refining codes (Emerson, Fretz, and Shaw 2011). Major themes emerged: uncertainty and confusion, negative impacts of restrictions on patients and providers, ethical dilemmas, varied interpretations, regional variation, and inequalities in access.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 180}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Indicators were developed iteratively during three rounds of engagement and consultations with 32 intermediaries from energy, housing, health and social service organizations operating at national and sub-national levels representing a diversity of constituents and locations. We engaged with 12 organizations one to three times over the course of the project in semi-structured 1-h long discussions. Stakeholders included: the Northern Territory Council of Social Service, the South Australian Council of Social Service, the Western Australian Council of Social Service, Original Power, the First Nations Clean Energy Network, Tangentyere Council Research Hub, Indigenous Consumer Assistance Network, Weipa Community Care, Energy Consumers Australia (ECA), Australian Energy Regulator and one other who requested anonymity. Before engagement commenced, these organizations all received a project information sheet and were read a consent form script; options were offered for anonymity, attribution at organizational level and attribution at individual level.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 181}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To design mid-century scenarios, we set varying levels of national mitigation effort, targeting the national total GHG emissions in 2050 to be 20%, 40%, 60%, 80% and 95% below 2005 levels, respectively. The 20-80% decarbonization results are presented in the main text, and 95% decarbonization results are presented in Supplementary Fig. 7 as a sensitivity run to understand the required energy system changes in line with a 1.5\u00b0C global climate stabilization target and close to the Biden Administration's net-zero emissions target. We assume linear GHG mitigation pathways from 2015 to 2050 with 5-year interval (see trajectories for GHG targets in Supplementary Fig. 1). Since GCAM-USA is embedded within the global GCAM model and allows for interactions between the United States and the rest of the world through global markets, to avoid cross-country carbon leakage, we set decarbonization targets for other countries based on ref. 53, which are consistent with the 2\u00b0C pathway. We consider three subnational policy approaches to achieve the national targets. Under the Uniform approach, the model solves a single MAC (and in turn carbon price) nationally to meet the decarbonization target. The MAC is uniform NATUrE CliMATE ChANGE across states, which is determined by the marginal cost to mitigate the last unit of CO2 emissions nationally. Under the Hybrid and Heterogeneous approaches, we allow for heterogeneous MACs across states. We set the relative ratio of state-level MACs based on the present-day public support level for climate policy, then let the model solve the whole set of MACs for 51 states (Figs. 1b and 2 and Supplementary Methods). Note that the MACs capture the effects similar to a carbon price. A high MAC encourages the deployment of high-cost CO2 mitigation technologies (such as renewable electricity and BECCS) as well as a reduction in overall fossil energy use. As long as the importing activities can reduce energy production and associated emissions within the state boundary, our approach would not further require importing only low-carbon electricity or goods.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 182}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Therefore, we explicitly model a representative technology for NETs. We characterize it as an investable technology in the model, such that each region can choose to reduce emissions with either standard abatement or via carbon removal. Since we explicitly model NETs, MIU is capped below 100%, meaning the investable technology is the only means to reach net-negative emissions. We choose to model our representative NET technology as DAC. DAC is modelled as in Realmonte et al.30 as an investable technology with depreciating capital, and emissions captured must be stored geologically. Total costs are divided into investment and variable costs (which implicitly include fuel and operation and maintenance costs), as well as storage costs. Total costs shrink with time due to learning by doing. The storage cost depends on the storage type (aquifer, exhausted oil and gas field, for instance) and each storage type has a regional cumulative capacity limit. No leakage is considered from the geological sites. See Supplementary Annex I for the implications of this representation on the shape of the marginal cost curve for abatement and removal.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 183}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    On the day of the study initiation, participants received a message instructing them to complete a pre-survey. At the end of the survey, they were given a personalized link to a web-based online climate betting site. Upon logging in to the site, they were presented with a number of climate betting markets and could take a position on any number of them (Fig. 1). In addition, participants could choose to trade a position with other participants. The number of available markets changed daily based on old markets closing and new markets opening. Participants could place multiple bets on the same market and could trade continuously before the bet's settle date and time. During the betting period, participants could log in to the prediction market site whenever they wished, monitor their currently available funds, view the available markets, make bets or trade positions. The market mechanism was 'double auction' (Supplementary Information), which required two participants to take opposite bets such that the sum of two bets was US$1 (that is, if one participant chose to wager US$0.60 that a 'Yes' bet will occur, only when another participant wagered US$0.40 that a 'No' on the outcome would a contract be initiated). If no participant was willing to take the opposite wager, the offer remained pending until the participant making the offer chose to revoke it. The manifested value of each market at any given moment was that of the last 'Yes' transaction to occur. That is, if a participant made a bet for US$0.82 that the average methane level in October 2018 will be the highest on record and another participant took the opposite position at US$0.12, then all participants saw the current market value as US$0.82. Accordingly, the values of markets represented the aggregated stable amount of money people were agreeing to wager on each topic. Naturally, as the settlement date of markets approached, the bets were likely to converge to the probability (0\u2026100) of the correct outcome (that is, if the market asked whether the number of disasters in a certain location be more than 10 by a certain date, and a few days before the closing time, a number of disasters already reached 9, the likelihood of a 'Yes' bet was higher). The betting period was initiated on 9 September 9 2018, and lasted until 11 November 11 2018. When the betting period was complete, participants were instructed to complete a post-survey. Once participants completed the post-survey, they were paid for their participation in the entire study. The pre- and post-surveys included a variety of questions (Supplementary Information provide all questions), but the main focus of the study was the subset of questions pertaining to the concern about climate change.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 184}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We have complied with all relevant ethical regulations. The interviews were conducted in Denmark by the Technical University of Denmark according to the guidelines. All interactions followed Chatham House rules. We have obtained informed consent from all interview participants.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 185}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    To estimate differences between the teacher-rated school behaviors and perceived selfcompetence outcomes of diagnosed and undiagnosed children, this study draws on the restricted-use Early Childhood Longitudinal Study-Kindergarten Cohort of 1998 (ECLS-K), an initially nationally representative sample of kindergarteners followed through middle school. The analytic sample used here consisted of the 7,330 children who remained in the study through 5th grade, were not missing data on either the outcomes or ADHD diagnosis, and were either diagnosed (N = 380) or plausible undiagnosed matches who had comparable levels of early ADHD-related behavioral problems in spite of not having been diagnosed (N = 6,950). Details on the longitudinal sample, attrition, and trimming are detailed in the Online Appendix; cell sizes were rounded to the nearest 10 per the restricted-use data agreement.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 186}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used SBTi's linear 1.5 \u00b0C and well below 2 \u00b0C global mitigation pathways41, involving annual reductions of 4.2% and 2.5% of base year emissions, respectively. The SBTi developed these pathways from a subset of the pathways described in the Special Report on Global Warming of 1.5 \u00b0C of the Intergovernmental Panel on Climate Change42. SBTi determined this subset by applying criteria related to temperature limit probability, temporary overshoot of emission budget, year of peak emissions and near-term emission reduction rate, with the aim of isolating pathways conforming with principles of plausibility, responsibility, objectivity, and consistency41. The SBTi notes that linearization of emission pathways over long timespans can result in substantial deviations of the pathways' cumulative emissions and therefore recommends the use of the derived reduction rates (4.2% and 2.5%) for the shorter time span of 2020-2035. However, the SBTi also advises companies to apply these reductions rates to set SBTs for base years before 20206, and SBTi applied the requirement of the 1.5 \u00b0C pathway (4.2% reduction in base year emissions per year) as a benchmark for the combined emission trajectory of companies with SBTs in the 2015-2019 period in its latest target progress report8. Following SBTi, we here apply the annual emission reduction rates of the two SBTi pathways (4.2% and 2.5%, respectively) as references to evaluate the Paris alignment of past corporate emission trajectories (2015-2019) and future targeted trajectories (median values 2017-2030) for the 115 companies.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 187}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    In the initial phase of this study, an extensive list of demand-side measures was identified, based on relevant literature and Ch. 5 of IPCC's AR6 WG III report2 (references in Table 1). To improve the credibility and policy relevance of the scenarios, and to ensure that no factors were overlooked, we collected input from experts in relevant areas related to climate change mitigation. This involved conducting an online stakeholder survey in 2021. Experts were asked by means of a questionnaire to evaluate the feasibility and effectiveness of different ways to reduce emissions in the domains of buildings, mobility and international transport (Supplementary Table 7). Details about the stakeholder survey are provided in Supplementary Information 2, and the responses are summarized in Supplementary Tables 7 and 8. This was used as input for designing the three intervention strategy scenarios. The full process of designing, simulating and analysing the scenarios is summarized in Supplementary Fig. 1.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 188}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We estimate GHG emissions associated with oil extraction using field-specific GHG emissions factors. We first estimate historical GHG emissions factors using the Oil Production Greenhouse Gas Emission Estimator (OPGEE) model v2.0 from the California Air Resources Board51,52 (Supplementary Fig. 10 provides 2015 data). The OPGEE model is an engineering-based life-cycle assessment tool for the measurement of GHG emissions from the production, processing and transport of crude oil. Using the OPGEE model and oil-extraction data from the California Department of Conservation, we model field-level GHG emissions for the years 2000, 2005, 2010, 2012, 2014, 2016 and 2018. We consider only upstream emissions from exploration, drilling, crude production, surface processing, maintenance operations, waste treatment/disposal and other small sources (as modelled by OPGEE). To obtain emissions factors for oil fields that were not modelled by OPGEE, we apply the median emissions factors for the fields that were modelled, separated by the use of steam injection (Supplementary Note 12  provides more information). To estimate the field-level GHG emissions for the projection period (2020-2045), we average the historical emissions factors for each year, again separated by fields based on the use of steam injection. We then linearly regress the average emissions factors and extrapolate over the projection period. Last, we apply the percent change in emissions factor between each forecast year to the field-level historical emissions factors from 2018 onwards to determine field-level emissions factors for each forecast year. Supplementary Note 12 provides more details.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 189}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Data were derived from two waves of the Canadian Quality of Work and Economic Life Study (C-QWELS), national surveys intended to examine social conditions and well-being among Canadians who were currently employed. Data were gathered by the study authors in cooperation with the Angus Reid Forum, a Canadian national survey research firm that maintains an ongoing national panel of Canadian respondents. The C-QWELS I was gathered from September 19 to September 24, 2019, and was an online survey conducted among a representative sample of 2,524 working Canadians. The response rate was 42%, but results were statistically weighted according to the most current education, age, gender, and region census data to ensure a sample representative of working Canadians. The C-QWELS II was conducted from March 17 to March 23, 2020 with another nationally representative sample of 2,528 working Canadians. The response rate was 43%, and responses were similarly weighted. Of the 5,052 total respondents, 4,923 were retained in the analytic sample (2019 sample = 2,477; 2020 sample = 2,446), a retention rate of over 97%, suggesting little bias due to listwise deletion.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 190}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Psychological distress was measured using five common symptoms of nonspecific psychological distress (Kessler et al. 2002): feel anxious or tense, feel nervous, feel restless or fidgety, feel sad or depressed, feel hopeless. Respondents indicated the frequency they experienced each symptom in the previous month, with response scales of all of the time, most of the time, some of the time, a little of the time, and none of the time. All responses were coded so that higher values indicated more frequent symptoms. Psychological distress was measured as the mean of responses to these five questions (Cronbach's alpha = .877).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 191}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    State-level data were compiled from administrative data sources (e.g., Bureau of Labor Statistics, Current Population Survey, Guttmacher Institute) to capture gender inequity in economic standing, political representation, policy protections, and reproductive rights. Table 1 includes a full list of measures with corresponding administrative data sources. Individual-level data came from the December 2014 to January 2019 waves of the Association of American Medical Colleges (AAMC) Consumer Survey of Health Care Access, a repeat cross-sectional, online survey of adults age 18 and older in the United States. Surveys were conducted by an external firm that maintains an active panel of potential study participants. Stratified sampling was used to collect data based on age and health insurance status, with oversamples of various subpopulations of interest (minority, rural, Medicaid recipients, etc.) in particular survey waves. U.S. census weights were available to account for nonprobability sampling procedures.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 192}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    Our data sources are defined in Table 1. We used home addresses to match adopter records at the address level to household-level variables for income, housing type and housing tenure purchased from Experian. Household-level incomes are estimated from individual- and household-level variables and a proprietary model developed by Experian, an empirically driven algorithm built to effectively predict sample statistics (for example, means, medians) of solar adopter incomes. The income estimates have been empirically validated in previous research on solar adopters13. The housing type variable is based on US Postal Service data. The housing tenure variable is based primarily on tax assessment and deed data. We predicted household-level racial characteristics using the 'wru' package in R36. The wru package estimates continuous probabilities for household race/ethnicity in five categories (Asian or Asian American, Black, Hispanic, White, other) based on the surname of the household's Census tract and the surname of the head of household. In cases where the surname was unavailable (12% of records), wru predicts race based only on the Census tract. Removing these tract-only predictions from the data does not substantially affect the results (Supplementary Fig. 2). The wru algorithm has been empirically validated to predict household race with around or above 80% accuracy5,37. We converted the continuous probabilities to a binary people of colour or Hispanic variable score based on whether some race other than White was assigned the greatest probability. We compare solar adopter demographics to the general population using state-level demographic statistics from the US Census American Community Survey. However, we omit the statewide comparison for race because the continuous race probabilities estimated by wru cannot be meaningfully compared to the self-identified races reported in Census data.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 193}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    All quantitative results in this work are obtained using the model LIMES-EU (Long-term Investment Model for the Electricity Sector), version 2.38. LIMES-EU is a linear optimization modelling framework that simultaneously determines cost-minimizing investment and dispatch decisions for generation, storage and transmission technologies in the European electricity sector. Although its clear focus is the electricity sector, the energy-intensive industry and district heating are also represented through marginal abatement cost curves. Compared with simple emissions trading models with static exogenous cost abatement curves, using an energy system model such as LIMES-EU allows to assess not only market developments (for example, prices or allowances in circulation) but also the investment dynamics and path dependencies within the electricity sector.LIMES-EU allows to fully simulate the EU ETS including the Market Stability Reserve (MSR)51. Hence, one can analyse figures such as the number of allowances in circulation, the intake by the MSR and resulting carbon prices. By varying the cap and MSR parameters, one can reproduce the state of the EU ETS between different political reforms.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 194}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The cluster analysis was performed using R 3.6.157 and the packages dplyr58, cluster59, factoextra60, ggplot261, Rtsne62, dbscan63, fpc64 and clustMixType65. Partitioning around medoids (PAM), hierarchical agglomerative clustering (HAC), density-based clustering and k-prototypes clustering were the four clustering methods applied to the dataset. We included different combinations of organization-level variables (for example, the legal structure of the organization) and project-level variables (for example, the type of energy activity and type of customer) in several analysis runs. The first run used all 48 variables, the second run omitted the variables for organization turnover and project location, and the third run omitted all the organization-level variables (such as turnover, number of members, number of volunteers, number of staff employed, ownership structure, charitable status and year of foundation) and project location, and used only the 40 variables relating to the operation of individual projects.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 195}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The CEEGE model is a dynamic computable equilibrium model of China, following the framework of the CHINAGEM model provided by the Centre of Policy Studies at Victoria University26,27. The CEEGE model is based on the neoclassical economics theory and assumes that the market is fully competitive and that the returns to scale of production are constant. It contains six economic agents (production, investment, consumption, government, foreign and inventory) and three primary factors (labour, capital and land) and is solved with the GEMPACK software51. In this model, a system of linearized equations is established to describe the behaviours of agents in response to price changes and determines the equilibrium price and quantity by equating the demand and supply for all goods and factors. The model can be used to capture the direct and indirect effects of exogenous changes in the economy and assess the impact mechanism across the economy. Hence, it provides a valuable tool for various policy-oriented studies related to carbon mitigation52,53. The modules of production, household consumption, governmental consumption, investment, export demand, carbon accounting and pricing, the dynamic module, the equilibrium mechanism, macro-economic closure and energy storage are presented in Supplementary Section 4.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 196}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used a two-level random intercept model to test our hypotheses. Our model nested annual state-level observations within states. In total, 611 observations (Level 1) were nested within the 50 states and the District of Columbia (Level 2) from 2006 to 2017. The two-level random intercept model, also known as the within-between random-effects model (REWB) or the hybrid model,2 allowed us to model the within and between effects for each driver of drug-related mortality. The model is written as follows: - - ij \u03b2 \u03b2 \u03b2 y x x x u e = + - + + + ij 0 1 2 ( ) . j j j ij b1 represents the within effects, which are estimated by group mean centering the variables, and b2 is the group mean, which represents the between effects. uj is the Level 2 error term, and eij is the Level 1 error term.3 The primary advantage of this model is that it allows the researcher to obtain both the within and between effects simultaneously. Doing so is not possible in the standard fixed-effects model, which relies on within variance only, or the standard  random-effects model, which uses a weighted average of within and between variance (Bell, Fairbrother, and Jones 2019). In the context of this study, it allowed us to test whether an increase in a driver within a state had the same effect as cross-sectional differences (the average level of the driver) between states.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 197}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    The sample was composed of men and women from the BRFSS national survey in 2018. BRFSS is the largest continuously conducted health survey in the world and collects annual, cross-sectional data from respondents in all 50 states about health behaviors and conditions and demographics. Some questions vary each year, thus we used 2018 data because it was the most recent year that had the most applicable and complete data on preventive health care use. It was also important to avoid 2020 data due to the impact of COVID-19 on health care use. Our analytic sample consisted of 425,454 individuals, of which 192,854 were men and 232,600 were women. The sample sizes varied for each preventive health care service outcome, depending on how many individuals responded to each of the questions.\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 198}
{"query": "You are given a passage from a scientific paper that describes part of the research study's methodology.\n\n    Summarize the method or approach using policy-brief style sentences. Your output should:\n    - Describe the model, data, or procedure mentioned in the passage\n    - Use clear and accessible language (technical terms are allowed when necessary)\n    - Focus only on what is present in the passage\n\n    Scientific Text:\n    We used the Panel Study of Income Dynamics (PSID), the longest running U.S. longitudinal survey, between 1970 and 2019. The PSID began with  a nationally representative sample of about 5,000 families and 18,000 individuals. Information from these individuals and their descendants was collected annually from 1968 to 1995 and biennially thereafter. The PSID was ideal for our purposes. The long-running administration of the PSID allows for the prospective tracking of individual employment characteristics, avoiding inaccuracies produced by retrospective accounting of one's career. Moreover, the PSID began collecting extensive health information of individuals in the 1990s. Main data came from the WZB-PSID file, which incorporates information from the Cross-National Equivalent File (Brady and Kohler 2022).\n\n    Summary:", "answer": "None (Use GPT-o3 as the judge).", "id": 199}