docs/appendices/paper_data/README.md

Primary Paper Data Extract

This folder organizes the four primary paper data sources referenced by PharmDrugBench. It is derived from server/data/benchmark.json, client/src/data/benchmarkContent.ts, and docs/appendices/sources/.

Files

• primary_papers.csv: one row per primary paper, with DOI/PMC, source URL, dataset scope, task count, task names, and source files.
• paper_task_map.csv: one row per paper-task mapping, including metrics and source status.
• paper_model_scores.csv: one row per paper-level dashboard score and model. Scores are fractions and percents when reported; blank score cells mean N/A.
• paper_task_scores.csv: one row per paper-task-model score. Blank score cells mean N/A, not zero.
• primary_paper_data.json: nested version of the same paper, task, and model-score data.

Primary papers

Paper ID	Paper	Dashboard metric	Tasks
rx-llm	Rx-Bench: a benchmarking suite to evaluate safe large language model performance for medication-related tasks	Rx-Bench (CMM)	6
ddi-identification	Drug-drug interaction identification using large language models	DDI Identification	3
medmatch	MedMatch: a first step for the automation of large language model performance benchmarking for medication-related tasks	MedMatch	7
drug-or-pokemon	Drug or Pokemon? Large language model performance in identification of fabricated medications	Drug or Pokémon?	2

Current public score policy

• Rx-Bench values come from docs/appendices/sources/rx_llm_tables_2_3.csv; the dashboard score is the macro mean of six primary CMM task metrics from Tables 2-3, and task-level rows are exposed separately.
• DDI identification values come from docs/appendices/sources/ddi_identification_table3.csv.
• MedGemma-27B is listed separately when Rx-Bench or DDI source tables report MedGemma rather than base Gemma 3 27B.
• MedMatch values are source-derived aggregates from entity_accuracy_table.csv and route_accuracy_table.csv; DrugGPT is not reported.
• Drug or Pokemon values are suspicion-detected scores, computed as 100 - default drug-dosing confabulation rate from the embedded PMC Table 2 rates; GPT-5 Chat and DrugGPT are not reported.
• The app also references LLM-Uncertainty-DDI as a supplemental DDI verification source, but this extract keeps it out of the four-primary-paper tables.