{"id":"W4239858202","doi":"10.1515/iupac.76.0199","title":"Cytochrome P450","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Cancer Treatment and Pharmacology","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Relation (database); Hazard; Computer science; Toxicology; Medicine; Chemistry; Pharmacology; Data mining; Biology; Linguistics; Philosophy","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":[],"consensus_categories":[],"category_scores_codex":[0.0009662671,0.001524058,0.001710277,0.003970944,0.0006654701,0.002226289,0.001527235,0.001137964,0.08317453],"category_scores_gemma":[0.007644608,0.0006303432,0.001344648,0.009010958,0.0002952005,0.001410815,0.001360772,0.001697103,0.07961123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001238888,"about_ca_system_score_gemma":0.002369074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01214673,"about_ca_topic_score_gemma":0.0182233,"domain_scores_codex":[0.998451,0.000260921,0.0003417684,0.0005099965,0.0003170387,0.0001192503],"domain_scores_gemma":[0.9968746,0.001082759,0.0005837177,0.000639207,0.0006198884,0.0001998078],"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":[0.0001860613,0.00002643379,0.002645382,0.003743938,0.0001109651,0.00006887046,0.00003225979,0.0002730793,0.0003437565,0.0008091037,0.9756631,0.01609713],"study_design_scores_gemma":[0.0001531673,0.00002449256,0.007679948,0.0008131112,0.00009712877,0.0002039571,0.00002904646,0.0001427229,0.0003126603,0.001272118,0.9892431,0.00002841736],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001488208,0.0004972355,0.0001326536,0.00005611676,0.00001813078,0.00001852966,0.9978865,0.0001930104,0.001049036],"genre_scores_gemma":[0.0005436254,0.000525275,0.0004211154,0.0001083507,0.00001154571,0.00009673247,0.9975268,0.0000531721,0.0007134242],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08317453,"threshold_uncertainty_score":0.2782465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02079004407645341,"score_gpt":0.4711151561286404,"score_spread":0.450325112052187,"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."}}