{"id":"W4253451054","doi":"10.1515/iupac.79.1785","title":"Pharmaceutical","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pharmaceutical studies and practices","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006160228,0.0004634893,0.0008921099,0.000117245,0.0001430223,0.00003820942,0.000233652,0.0003666902,0.02086618],"category_scores_gemma":[0.001260854,0.0002938613,0.0002721682,0.0001738686,0.0002668611,0.00008628784,0.0002652851,0.001121897,0.00002545004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003786155,"about_ca_system_score_gemma":0.000575933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003343043,"about_ca_topic_score_gemma":0.00004042944,"domain_scores_codex":[0.9969176,0.00009839363,0.0004827135,0.0005423803,0.00133602,0.0006229009],"domain_scores_gemma":[0.9978756,0.0003647755,0.0001837549,0.000577512,0.0004277059,0.0005706597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001392985,0.0005010832,0.00002006142,0.0003995507,0.0005315202,0.0004894069,0.00000325992,2.730695e-8,0.00002570158,0.000007900065,0.9743924,0.02223617],"study_design_scores_gemma":[0.002805216,0.0003877838,0.00003621769,0.000466251,0.001263462,0.0001555416,0.00001102428,0.000004993823,0.00006158976,0.00004337455,0.9944039,0.0003606312],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003411917,0.005489188,0.00002936685,0.01473095,0.0009528345,0.0004239317,0.9774309,0.00008500158,0.0008237297],"genre_scores_gemma":[0.00002572772,0.0193039,0.00003916062,0.00533423,0.002641234,0.00001737433,0.9717773,0.00004008443,0.0008210288],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02187553,"threshold_uncertainty_score":0.9999514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06662407115309771,"score_gpt":0.5363999356504291,"score_spread":0.4697758644973314,"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."}}