{"id":"W4409317481","doi":"10.1126/science.adx0339","title":"AI drug development’s data problem","year":2025,"lang":"en","type":"editorial","venue":"Science","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for International Governance Innovation","funders":"","keywords":"Computer science; Drug discovery; Field (mathematics); Data science; Drug development; Quality (philosophy); Artificial intelligence; Drug; Medicine; Bioinformatics; Pharmacology; Biology; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02009827,0.002250207,0.00240564,0.003180942,0.002923782,0.008546843,0.003129831,0.01900608,0.008210563],"category_scores_gemma":[0.06042985,0.0008824777,0.002394943,0.001642463,0.005667078,0.007157043,0.001986326,0.03588212,0.007624644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004312484,"about_ca_system_score_gemma":0.006885512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002716163,"about_ca_topic_score_gemma":0.005317739,"domain_scores_codex":[0.9887621,0.003028188,0.001309508,0.001236086,0.005263376,0.0004007957],"domain_scores_gemma":[0.932317,0.04617488,0.001429422,0.001633053,0.0150734,0.003372277],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001618549,0.000005569434,0.00001453752,0.00009924882,0.00001544861,0.00004454627,0.00001196788,0.00002647745,0.00001666757,0.00268519,0.989053,0.008011156],"study_design_scores_gemma":[0.00004152165,0.00001263752,0.00006613586,0.0002465922,0.00002312745,0.0001208125,0.00001761452,0.0001380925,0.00004908148,0.004892554,0.9943777,0.0000141326],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00004654556,0.01793302,0.0007389961,0.2484069,0.7289202,0.00002916179,0.0001418169,0.00008140715,0.003701868],"genre_scores_gemma":[0.001100159,0.01195247,0.0007863611,0.186177,0.7886225,0.00006472224,0.00008337237,0.00008224058,0.01113126],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.9799017,"threshold_uncertainty_score":0.1062911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02487313314061693,"score_gpt":0.3604463068627179,"score_spread":0.3355731737221009,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}