{"id":"W4253691899","doi":"10.1515/iupac.79.0834","title":"Antimuscarinic","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Toxicology; Computer science; Library science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000914965,0.001301762,0.001814389,0.002977973,0.0004759893,0.00174571,0.001699358,0.001532232,0.06635815],"category_scores_gemma":[0.008297984,0.0004091778,0.001734879,0.004410176,0.0002403006,0.001234049,0.001119049,0.001453008,0.04898153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001220125,"about_ca_system_score_gemma":0.002220918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0103463,"about_ca_topic_score_gemma":0.02489697,"domain_scores_codex":[0.9988398,0.0001865231,0.0002802031,0.0003439586,0.0002458961,0.000103644],"domain_scores_gemma":[0.9972482,0.0009009386,0.0006224704,0.0004544437,0.0006112256,0.0001627842],"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":[0.001172001,0.0000783272,0.0048793,0.01027145,0.0003819036,0.00008405727,0.00002476179,0.000564803,0.0004983617,0.0008751688,0.946198,0.03497174],"study_design_scores_gemma":[0.0009624741,0.0001208589,0.01387143,0.002139711,0.0004876062,0.0003087703,0.0000396519,0.0003730207,0.0007005387,0.001790025,0.9791589,0.00004689156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004484812,0.001430576,0.0001034283,0.0001178718,0.00003786876,0.00003917872,0.9956437,0.0001496228,0.002029247],"genre_scores_gemma":[0.001887966,0.001304717,0.000605439,0.0003652125,0.00003311965,0.0001890769,0.9936519,0.00004810887,0.001914555],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06635815,"threshold_uncertainty_score":0.2219901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005930550451228722,"score_gpt":0.329141757463,"score_spread":0.3232112070117713,"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."}}