The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 2 fields in line 6, saw 6
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 198, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
nrows
^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 2 fields in line 6, saw 6Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Supplement FDA Adverse Event 2014-2024 Decade Audit
A modeled 10-year audit of US dietary supplement adverse events, organized against the FDA CFSAN Adverse Event Reporting System (CAERS) framework, 2014-01-01 through 2024-12-31. The figures are analyzed aggregates calibrated against published CAERS-derived literature — directional estimates, not a live extract of raw CAERS records (see Data provenance below). Organized by 14 ingredient categories, severity tier, top reactions, and (where publicly attributable) brand and ingredient flags.
- License: CC-BY 4.0
- DOI: 10.5281/zenodo.20632389
- Source study: https://healthbritannica.com/research/supplement-adverse-event-2014-2024/
- Author: Vincent Wesley Couey (ORCID 0009-0005-6869-308X) · published via Health Britannica (healthbritannica.com), part of the Lattice research network.
What's in it
Files: data.json, caers-supplement-adverse-events-by-category-2014-2024.csv, caers-supplement-adverse-events-trends-severity-ingredients-2014-2024.csv. Main table categories (14 rows): category, total_reports_2014_2024, serious_outcome_count, serious_outcome_pct, top_reactions, top_ingredients, top_brands_publicly_named, trend_2014_to_2024_pct_change, source_caers_url.
Data provenance (read before citing)
This dataset is MODELED, not extracted. The numeric values in the tables (per-category report counts, serious-outcome percentages, 2014→2024 trends) are analyzed aggregates calibrated against published CAERS-derived literature — e.g., Geller et al. (NEJM 2015) and FDA/CFSAN summary analyses — applied through the 14-category supplement taxonomy below. They are directional estimates, not exact counts extracted from raw FDA CAERS quarterly files.
- Sourced (verifiable): the FDA CAERS system and the published peer-reviewed CAERS analyses the estimates are calibrated against; the FDA serious-outcome definitions (death / life-threatening / hospitalization / disability / congenital-anomaly / required-intervention); the 14-category taxonomy (vitamins, minerals, herbal/botanicals, weight-loss, sports/bodybuilding, immune, digestive/probiotic, sexual-health, sleep/relaxation, energy/stimulant, CBD/cannabinoid, hormones/precursors, multivitamins, MLM-distributed brands, other).
- Modeled / estimated: every numeric value in the tables (category counts, severity %, trend %). Mixed-category products are counted toward each applicable category, so category totals sum above the unique-record total.
- NOT a live extract: this is not a download of raw CAERS files. For the official raw quarterly CAERS data, see https://www.fda.gov/food/compliance-enforcement-food/cfsan-adverse-event-reporting-system-caers. Do not quote these figures as exact FDA record counts.
(This same provenance statement appears on the study page and in data.json. CAERS is voluntary and captures an FDA-estimated 1–10% of true events; reports do not establish causation.)
Citation
Couey, V. W. (2026). Supplement FDA Adverse Event 2014-2024 Decade Audit [Data set]. Health Britannica. https://doi.org/10.5281/zenodo.20632389
CC-BY 4.0 — free to use with attribution. Informational and research use only. Not medical advice; verify against the primary source and a licensed professional before relying on any value. Dated snapshot; verify current values before relying on them.
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