{"id":"W2001314811","doi":"10.1038/nchembio0709-436","title":"Open access chemical and clinical probes to support drug discovery","year":2009,"lang":"en","type":"article","venue":"Nature Chemical Biology","topic":"Pharmacogenetics and Drug Metabolism","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":132,"is_retracted":false,"has_abstract":false,"ca_institutions":"Structural Genomics Consortium; University of Toronto","funders":"Canadian Institutes of Health Research; Wellcome Trust","keywords":"Drug discovery; Pharmaceutical industry; Productivity; Data science; Business; Drug industry; Computational biology; Computer science; Biology; Biotechnology; Bioinformatics; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["open_science"],"domain":null,"study_design":"not_applicable","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["open_science","scholarly_communication"],"domain":null,"study_design":"design_other","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0009726431,0.0003523838,0.0006642779,0.00008946157,0.0001007943,0.0001813136,0.00224311,0.001389735,0.000446682],"category_scores_gemma":[0.0004870805,0.0002885174,0.0001467608,0.0002815676,0.0003460156,0.0003064798,0.001916398,0.002484904,0.00007566068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003542399,"about_ca_system_score_gemma":0.0001333867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006378462,"about_ca_topic_score_gemma":0.000001946804,"domain_scores_codex":[0.9973547,0.0003024321,0.00061134,0.0009277374,0.0001134371,0.0006903628],"domain_scores_gemma":[0.9982563,0.0004858274,0.000136933,0.000309757,0.0001048558,0.0007063344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009919782,0.000704637,0.01416758,0.00001522682,0.0001395384,0.00002857764,0.0000732976,0.000001018624,0.7873629,0.005056832,0.05536571,0.1360927],"study_design_scores_gemma":[0.002005464,0.0001150356,0.002729224,0.000006801678,0.0001322516,0.00003150999,0.000006475084,0.00003343862,0.5688101,0.007195745,0.4185392,0.0003947646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767361,0.001414241,0.00002079866,0.01110415,0.001459136,0.0007347016,0.0001496914,0.00007400609,0.008307201],"genre_scores_gemma":[0.9497935,0.0006766926,0.0007257066,0.04703065,0.001094645,0.00003906109,0.0001442027,0.00002081119,0.0004747339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3631735,"threshold_uncertainty_score":0.9999567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.134351923613858,"score_gpt":0.5619974727123195,"score_spread":0.4276455490984615,"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."}}