{"id":"W4238143845","doi":"10.1515/iupac.79.0909","title":"Biochemical Mechanism","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Hazard; Toxicology; Chemistry; Philosophy; Biology; Linguistics","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":[0.0001883956,0.0006142679,0.000624495,0.00006420767,0.0001463608,0.0000309273,0.0008333766,0.0008634646,0.055551],"category_scores_gemma":[0.0004336519,0.0005202593,0.0002385067,0.00007848092,0.0002240796,0.00006677789,0.0002785156,0.0008360209,0.000009928029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009271714,"about_ca_system_score_gemma":0.0005456514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006825534,"about_ca_topic_score_gemma":0.000007862766,"domain_scores_codex":[0.9969885,0.00001395498,0.0005520342,0.0008126278,0.001073677,0.0005592362],"domain_scores_gemma":[0.997765,0.00007978165,0.0003252092,0.001334518,0.0002268653,0.0002686182],"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":[0.0000902359,0.000232927,2.487066e-7,0.000592764,0.0001034977,0.0001118285,0.000003463565,8.495264e-8,0.03110615,0.00001663893,0.966736,0.001006224],"study_design_scores_gemma":[0.0007852619,0.00001944475,1.29771e-8,0.0006876132,0.0001011729,0.00002436788,0.00001281013,4.556278e-7,0.08010489,0.0005177692,0.9171337,0.0006124902],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001298747,0.0007172709,0.0001046549,0.000103474,0.0006277408,0.00005601428,0.99679,0.0001329588,0.001338033],"genre_scores_gemma":[0.00001953318,0.0006409262,0.0001243633,0.000180543,0.002051938,0.0000239639,0.9900571,0.00006379319,0.006837853],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05554108,"threshold_uncertainty_score":0.9997249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01196565677440012,"score_gpt":0.3748283550210018,"score_spread":0.3628626982466017,"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."}}