Upload KAUBioMED-LLM LoRA adapter and manuscript evidence package

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+adapter/tokenizer.json filter=lfs diff=lfs merge=lfs -text

INFERENCE.md

@@ -0,0 +1,12 @@
+# Inference example
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+base = 'meta-llama/Llama-3.1-8B-Instruct'
+adapter = './adapter'
+tok = AutoTokenizer.from_pretrained(base)
+model = AutoModelForCausalLM.from_pretrained(base, device_map='auto')
+model = PeftModel.from_pretrained(model, adapter)
+```

README.md

@@ -0,0 +1,72 @@
+---
+license: llama3.1
+base_model:
+  - meta-llama/Llama-3.1-8B-Instruct
+  - Qwen/Qwen2.5-1.5B-Instruct
+tags:
+  - biomedical
+  - genomics
+  - variant-interpretation
+  - lora
+  - research
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# KAUBioMED-LLM
+
+KAUBioMED-LLM is a research prototype for guarded biomedical variant interpretation plus leakage-aware temporal variant scoring.
+
+## Components
+
+- Qwen2.5-1.5B-Instruct v0.1: lightweight prototype report generator.
+- Llama-3.1-8B-Instruct v0.2: stronger guarded report-generation baseline.
+- score_model: scikit-learn HistGradientBoostingClassifier with isotonic calibration, using label-free broad variant features.
+
+## Intended Use
+
+Research use only. Not for clinical diagnosis, treatment decisions, or patient management.
+
+## Data and Provenance
+
+See `reports/DATA_PROVENANCE.md`.
+
+## Key Results
+
+First-appearance temporal broad score_model test:
+
+- AUROC: 0.99125
+- AUPRC: 0.96938
+- Brier: 0.02903
+- ECE 10-bin: 0.03428
+
+Missense-only limitation:
+
+- score_model v0 missense AUROC: 0.78497
+- missense v1 protein-feature AUROC: 0.83644
+- AlphaMissense same-row AUROC: 0.97214
+- REVEL same-row AUROC: 0.97832
+
+## Known Limitations
+
+- Broad AUROC is driven partly by easy consequence classes; see `reports/score_model/per_consequence_breakdown.md`.
+- Missense performance remains below REVEL and AlphaMissense.
+- Evidence panel is limited to 20 genes and is not genome-wide.
+- Calibration is measured on a first-appearance ClinVar temporal split, not prospective clinical data.
+- Not validated for clinical deployment.
+
+## Base Model Attribution and License Notes
+
+Llama-derived artifacts are subject to the Meta Llama 3.1 Community License and Acceptable Use Policy. Qwen-derived prototype artifacts are subject to Qwen2.5 license terms. Verify license terms before public release.
+
+## Reproducibility Commands
+
+```bash
+cd /ddn/data/generic/bbabajan/KAUBioMED_LLM
+/ddn/data/generic/bbabajan/envs/kaubiomed-llm/bin/python pipeline/build_label_free_features.py
+/ddn/data/generic/bbabajan/envs/kaubiomed-llm/bin/python pipeline/train_label_free_score_model.py
+/ddn/data/generic/bbabajan/envs/kaubiomed-llm/bin/python pipeline/evaluate_first_appearance_temporal.py
+/ddn/data/generic/bbabajan/envs/kaubiomed-llm/bin/python pipeline/compare_external_predictors_first_appearance.py
+/ddn/data/generic/bbabajan/envs/kaubiomed-llm/bin/python pipeline/kaubiomed_full_report.py
+/ddn/data/generic/bbabajan/envs/kaubiomed-llm/bin/python pipeline/apply_report_guards.py
+```

UPLOAD_READINESS.md

@@ -0,0 +1,65 @@
+{
+  "status": "prepared_not_pushed",
+  "file_count": 11,
+  "files": [
+    {
+      "path": "README.md",
+      "size": 2526
+    },
+    {
+      "path": "INFERENCE.md",
+      "size": 350
+    },
+    {
+      "path": "UPLOAD_READINESS.md",
+      "size": 3562
+    },
+    {
+      "path": "reports/DATA_PROVENANCE.md",
+      "size": 3512
+    },
+    {
+      "path": "reports/manuscript/TABLES.md",
+      "size": 5325
+    },
+    {
+      "path": "adapter/README.md",
+      "size": 5342
+    },
+    {
+      "path": "adapter/adapter_model.safetensors",
+      "size": 167832240
+    },
+    {
+      "path": "adapter/tokenizer_config.json",
+      "size": 352
+    },
+    {
+      "path": "adapter/chat_template.jinja",
+      "size": 4614
+    },
+    {
+      "path": "adapter/tokenizer.json",
+      "size": 17210019
+    },
+    {
+      "path": "adapter/adapter_config.json",
+      "size": 1173
+    }
+  ],
+  "base_weights_excluded": true,
+  "base_weight_hits": [],
+  "secret_token_hits": [],
+  "checkpoint_optimizer_files_excluded": true,
+  "human_push_commands": [
+    "cd /ddn/data/generic/bbabajan/KAUBioMED_LLM/release/hf_upload_kaubiomed",
+    "huggingface-cli login",
+    "huggingface-cli upload <YOUR_REPO_ID> . . --repo-type model"
+  ],
+  "human_checklist": [
+    "Review README.md disclaimer/license/base attribution",
+    "Confirm adapter-only upload",
+    "Confirm repository visibility",
+    "Do not upload base Llama/Qwen weights"
+  ]
+}

adapter/README.md

@@ -0,0 +1,207 @@
+---
+base_model: /ddn/data/generic/bbabajan/KAUBioMED_LLM/models/hf_snapshots/meta-llama__Llama-3.1-8B-Instruct
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:/ddn/data/generic/bbabajan/KAUBioMED_LLM/models/hf_snapshots/meta-llama__Llama-3.1-8B-Instruct
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.19.1

adapter/adapter_config.json

@@ -0,0 +1,48 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "/ddn/data/generic/bbabajan/KAUBioMED_LLM/models/hf_snapshots/meta-llama__Llama-3.1-8B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "up_proj",
+    "gate_proj",
+    "q_proj",
+    "o_proj",
+    "down_proj",
+    "k_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:70227608a9a614d565207345f63d362cf6c6959e56fe542741f6f6fbd8005c2e
+size 167832240

adapter/chat_template.jinja

@@ -0,0 +1,109 @@
+{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = true %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- set date_string = "26 Jul 2024" %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content']|trim %}
+    {%- set messages = messages[1:] %}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{#- System message + builtin tools #}
+{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
+{%- if builtin_tools is defined or tools is not none %}
+    {{- "Environment: ipython\n" }}
+{%- endif %}
+{%- if builtin_tools is defined %}
+    {{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
+{%- endif %}
+{{- "Cutting Knowledge Date: December 2023\n" }}
+{{- "Today Date: " + date_string + "\n\n" }}
+{%- if tools is not none and not tools_in_user_message %}
+    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+{%- endif %}
+{{- system_message }}
+{{- "<|eot_id|>" }}
+
+{#- Custom tools are passed in a user message with some extra guidance #}
+{%- if tools_in_user_message and not tools is none %}
+    {#- Extract the first user message so we can plug it in here #}
+    {%- if messages | length != 0 %}
+        {%- set first_user_message = messages[0]['content']|trim %}
+        {%- set messages = messages[1:] %}
+    {%- else %}
+        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
+{%- endif %}
+    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
+    {{- "Given the following functions, please respond with a JSON for a function call " }}
+    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+    {{- first_user_message + "<|eot_id|>"}}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- "<|python_tag|>" + tool_call.name + ".call(" }}
+            {%- for arg_name, arg_val in tool_call.arguments | items %}
+                {{- arg_name + '="' + arg_val + '"' }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- endif %}
+                {%- endfor %}
+            {{- ")" }}
+        {%- else  %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- '{"name": "' + tool_call.name + '", ' }}
+            {{- '"parameters": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- "}" }}
+        {%- endif %}
+        {%- if builtin_tools is defined %}
+            {#- This means we're in ipython mode #}
+            {{- "<|eom_id|>" }}
+        {%- else %}
+            {{- "<|eot_id|>" }}
+        {%- endif %}
+    {%- elif message.role == "tool" or message.role == "ipython" %}
+        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
+        {%- if message.content is mapping or message.content is iterable %}
+            {{- message.content | tojson }}
+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
+{%- endif %}

adapter/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c6766e36c60cb5740c4f16f2d3b75e19c5ea783b6bb682f6346e524ecd34d79d
+size 17210019

adapter/tokenizer_config.json

@@ -0,0 +1,15 @@
+{
+  "backend": "tokenizers",
+  "bos_token": "<|begin_of_text|>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "is_local": true,
+  "local_files_only": true,
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|eot_id|>",
+  "tokenizer_class": "TokenizersBackend"
+}

reports/DATA_PROVENANCE.md

@@ -0,0 +1,91 @@
+# KAUBioMED-LLM Data Provenance
+
+Date prepared: 2026-06-15
+
+This file records sources actually present or used in the HPC project. Unknown versions are explicitly marked as not recorded rather than guessed.
+
+## ClinVar Snapshots
+
+### ClinVar train snapshot
+
+- Path: `/ddn/data/generic/bbabajan/KAUBioMED_LLM/data/raw/clinvar/archive_2.0/2023/clinvar_20231226.vcf.gz`
+- Exists: `True`
+- Size bytes: `90917025`
+- MD5: `c1c17cb968c413c1809cb445347f051f`
+- URL: https://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/archive_2.0/2023/clinvar_20231226.vcf.gz
+
+### ClinVar future/test snapshot
+
+- Path: `/ddn/data/generic/bbabajan/KAUBioMED_LLM/data/raw/clinvar/archive_2.0/2025/clinvar_20251221.vcf.gz`
+- Exists: `True`
+- Size bytes: `181881189`
+- MD5: `0e9b0df5bc2f82334df20a3c61dd2494`
+- URL: https://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/archive_2.0/2025/clinvar_20251221.vcf.gz
+
+## ClinVar Tab-Delimited Metadata
+
+### variant_summary.txt.gz
+
+- Path: `/ddn/data/generic/bbabajan/KAUBioMED_LLM/data/raw/clinvar/variant_summary.txt.gz`
+- Exists: `True`
+- Size bytes: `439336125`
+- MD5: `0b1abcb00498745b05236fa7f7612b8c`
+- URL: https://ftp.ncbi.nlm.nih.gov/pub/clinvar/tab_delimited/variant_summary.txt.gz
+
+### submission_summary.txt.gz
+
+- Path: `/ddn/data/generic/bbabajan/KAUBioMED_LLM/data/raw/clinvar/submission_summary.txt.gz`
+- Exists: `True`
+- Size bytes: `381965640`
+- MD5: `8926e17b9911c6388b2363c268d8de8e`
+- URL: https://ftp.ncbi.nlm.nih.gov/pub/clinvar/tab_delimited/submission_summary.txt.gz
+
+## Allele Frequency Sources
+
+- gnomAD: not used in the current score_model feature table.
+- Current model uses ClinVar VCF INFO fields `AF_ESP`, `AF_EXAC`, and `AF_TGP` when present.
+- gnomAD version: not applicable for current results.
+
+## UniProt / PubMed Evidence
+
+- Evidence file: `/ddn/data/generic/bbabajan/KAUBioMED_LLM/knowledge/kaubiomed_gene_evidence.jsonl`
+- Exists: `True`
+- Size bytes: `253848`
+- Access date/version: version not recorded — verify before submission.
+- Scope: 20-gene evidence panel, not genome-wide.
+
+## AlphaFold DB
+
+- Manifest: `/ddn/data/generic/bbabajan/KAUBioMED_LLM/knowledge/alphafold/alphafold_manifest.jsonl`
+- Exists: `True`
+- Size bytes: `12754`
+- Access date/model version: version not recorded — verify before submission.
+
+## Ensembl VEP REST
+
+- Mapper script: `/ddn/data/generic/bbabajan/KAUBioMED_LLM/pipeline/vep_residue_mapper.py`
+- Exists: `True`
+- REST service/version/date: version not recorded — verify before submission.
+- Mapping policy: MANE-preferred, HGVS protein required, UniProt reconciliation required, abstain on mismatch.
+
+## Base LLM Snapshots
+
+### Qwen2.5-1.5B-Instruct
+
+- Snapshot path: `/ddn/data/generic/bbabajan/KAUBioMED_LLM/models/hf_snapshots/Qwen__Qwen2.5-1.5B-Instruct`
+- Exists: `True`
+- Recorded revision: revision not recorded
+- Base model ID: Qwen/Qwen2.5-1.5B-Instruct
+- License: verify before public release.
+
+### Llama-3.1-8B-Instruct
+
+- Snapshot path: `/ddn/data/generic/bbabajan/KAUBioMED_LLM/models/hf_snapshots/meta-llama__Llama-3.1-8B-Instruct`
+- Exists: `True`
+- Recorded revision: revision not recorded
+- Base model ID: meta-llama/Llama-3.1-8B-Instruct
+- License: Meta Llama 3.1 Community License applies to Llama-derived adapter/merged artifacts; verify current license text before public release.
+
+## Score Model Feature Boundaries
+
+Manuscript-facing score_model features exclude AlphaMissense, REVEL, CADD, UVPS, KAUBioMED LLM scores, ClinVar clinical-significance text, and ClinVar review-status/review_stars.

reports/manuscript/TABLES.md

@@ -0,0 +1,106 @@
+# Manuscript Tables
+
+## Table 1. Broad Model First-Appearance Temporal Metrics
+
+Caption: No-review-status broad score_model evaluated on variants first appearing between ClinVar 2023-12-26 and 2025-12-21.
+
+| Split | N | AUROC | AUPRC | Brier | ECE |
+|---|---:|---:|---:|---:|---:|
+| first-appearance temporal | 509974 | 0.99125 | 0.96938 | 0.02903 | 0.03428 |
+
+## Table 2. Per-Consequence Breakdown
+
+Caption: Same first-appearance split; low-N classes are aggregated.
+
+| Consequence | N | Pos | Neg | AUROC | AUPRC | Brier | ECE |
+|---|---:|---:|---:|---:|---:|---:|---:|
+| non-coding_transcript_variant | 34607 | 257 | 34350 | 0.91551 | 0.61517 | 0.00398 | 0.00219 |
+| 3_prime_UTR_variant | 3861 | 24 | 3837 | 0.89588 | 0.13295 | 0.00623 | 0.00464 |
+| other (low-N) | 534 | 336 | 198 | 0.87042 | 0.90320 | 0.13473 | 0.05293 |
+| unknown | 1503 | 542 | 961 | 0.86056 | 0.75580 | 0.14478 | 0.05336 |
+| missense_variant | 67847 | 12943 | 54904 | 0.81292 | 0.55438 | 0.18069 | 0.23174 |
+| splice_donor_variant | 8438 | 8238 | 200 | 0.81240 | 0.99205 | 0.01565 | 0.00245 |
+| 5_prime_UTR_variant | 6609 | 68 | 6541 | 0.77156 | 0.23015 | 0.00891 | 0.00739 |
+| inframe_deletion | 386 | 219 | 167 | 0.76963 | 0.80047 | 0.20247 | 0.08748 |
+| initiator_codon_variant | 713 | 615 | 98 | 0.74360 | 0.93131 | 0.09672 | 0.04770 |
+| intron_variant | 153601 | 951 | 152650 | 0.73241 | 0.03627 | 0.00619 | 0.00863 |
+| frameshift_variant | 38296 | 37947 | 349 | 0.72617 | 0.99567 | 0.00786 | 0.00094 |
+| nonsense | 22375 | 22034 | 341 | 0.70115 | 0.99182 | 0.01238 | 0.00779 |
+| splice_acceptor_variant | 7209 | 7081 | 128 | 0.70025 | 0.98999 | 0.01468 | 0.00421 |
+| synonymous_variant | 163995 | 121 | 163874 | 0.64395 | 0.00175 | 0.00074 | 0.00078 |
+
+## Table 3. External Comparator, All-Variant Overlap
+
+Caption: First-appearance temporal overlap where Project 1 external annotations exist; AlphaMissense/REVEL coverage is limited by design.
+
+| Model | N | AUROC | AUPRC | Brier |
+|---|---:|---:|---:|---:|
+| score_model v0 | 27850 | 0.98520 | 0.98167 | 0.04545 |
+| CADD PHRED | 27850 | 0.99209 | 0.99086 | 0.18824 |
+| AlphaMissense | 4988 | 0.97183 | 0.98189 | 0.07705 |
+| REVEL | 6275 | 0.95642 | 0.97127 | 0.09579 |
+
+## Table 4. External Comparator, Missense-Only
+
+Caption: First-appearance temporal missense-only comparison; AlphaMissense and REVEL are missense-oriented predictors.
+
+| Model | N | AUROC | AUPRC | Brier |
+|---|---:|---:|---:|---:|
+| score_model v0 | 5220 | 0.78497 | 0.83876 | 0.18825 |
+| missense v1 | 5018 | 0.83644 | 0.87361 | 0.20575 |
+| CADD PHRED | 5220 | 0.94829 | 0.95653 | 0.15822 |
+| AlphaMissense | 4965 | 0.97209 | 0.98214 | 0.07687 |
+| REVEL | 5140 | 0.97769 | 0.98612 | 0.06937 |
+
+## Table 5. Qwen v0.1 vs Llama v0.2 Report Generation
+
+Caption: Structured report-generation comparison; see source comparison report for full details.
+
+# KAUBioMED-LLM Qwen v0.1 vs Llama v0.2 Comparison
+
+Date: 2026-06-15
+
+## Scientific Position
+
+This comparison evaluates two KAUBioMED-LLM report-generation models under the same score-schema and guarded-report framework. The current kaubiomed_score remains an evidence-label score for report organization, not a leakage-free calibrated pathogenicity probability.
+
+## Summary Table
+
+| Metric | Qwen v0.1 | Llama v0.2 |
+|---|---:|---:|
+| Base model | Qwen2.5-1.5B-Instruct | Llama-3.1-8B-Instruct |
+| Base/snapshot size | 2.89 GB | 29.93 GB |
+| Adapter path | models/kaubiomed_qwen2p5_1p5b_lora_calibrated | models/kaubiomed_llama31_8b_lora_score_schema |
+| Adapter size | 304.0 MB | 1.14 GB |
+| Training records | 910 | 910 |
+| Validation records | 101 | 101 |
+| Epochs | 1 | 2 |
+| Train loss | 0.0475554999552275 | 0.22699994018726183 |
+| Eval loss | 0.04750876873731613 | 0.0603446401655674 |
+| 50-example raw strict JSON | not separately measured for calibrated Qwen | 50/50 (1.0) |
+| Fresh strict valid | 5/5 | 5/5 |
+| Fresh repaired records | NA | 0 |
+| Citation guard pass | 5/5 | 5/5 |
+| Structure mapping OK | 1/5 | 1/5 |
+| Structure abstained | 4 | 4 |
+| Fresh inference runtime | not consistently recorded in final Qwen summary | 114.12 sec |
+
+## Interpretation
+
+- Qwen v0.1 remains the lightweight reproducible prototype baseline.
+- Llama v0.2 is the stronger structured-output candidate: it achieved 50/50 raw strict JSON on validation and 5/5 raw strict JSON on fresh variants without repair.
+- Both models pass citation and abstention guards on the 5 fresh reports.
+- Structure behavior is identical because structure mapping is evidence-layer dependent, not base-model dependent: 1/5 fresh variants map to a reconciled missense residue; 4/5 correctly abstain.
+- Llama is larger and more expensive, so it should be positioned as a stronger v0.2 candidate rather than simply replacing Qwen without cost discussion.
+
+## Recommendation
+
+Use Qwen v0.1 as the lightweight baseline and Llama v0.2 as the preferred high-capability report-generation model. The next scientific step is not another base-model swap; it is the leakage-free score_model and temporal validation benchmark.
+
+## Required Next Work
+
+1. Build label-free feature tables without ClinVar-derived prompt labels.
+2. Train a separate score model on clean features.
+3. Run temporal ClinVar validation with AUROC, AUPRC, Brier, and ECE.
+4. Add the benchmark results to the manuscript and model card.
+