{"id":"W4249308546","doi":"10.1515/iupac.87.0054","title":"Antispasmodic","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Plant-based Medicinal Research","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Psychology; Chemistry; Linguistics; Philosophy; Data mining; 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":[0.0007243282,0.0009076068,0.001231561,0.002764799,0.0004188681,0.001320012,0.0009065208,0.001009658,0.06557357],"category_scores_gemma":[0.006452919,0.0003403085,0.001774957,0.004252541,0.0002796268,0.001376316,0.0008520782,0.001633121,0.029415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009153538,"about_ca_system_score_gemma":0.002010045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005882488,"about_ca_topic_score_gemma":0.01536192,"domain_scores_codex":[0.9987549,0.0001782192,0.0004510539,0.000286791,0.0002401818,0.00008900915],"domain_scores_gemma":[0.9972735,0.0009897517,0.0007925069,0.0003520162,0.0004687672,0.0001234735],"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":[0.002596992,0.0001474281,0.008770052,0.02316249,0.0004831673,0.0002104546,0.0000588995,0.0007827511,0.001037343,0.001871528,0.8492821,0.1115968],"study_design_scores_gemma":[0.0007952183,0.0001285579,0.01533424,0.002807607,0.0003033604,0.0004030537,0.00004430816,0.000285316,0.0006181215,0.001966575,0.9772748,0.00003885951],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001399309,0.003200507,0.0002825505,0.0002210302,0.00008899906,0.0001203954,0.9877161,0.0002735308,0.006697532],"genre_scores_gemma":[0.00621434,0.005078822,0.001774845,0.0008155511,0.00008163663,0.0004419801,0.9800153,0.0001145808,0.005462936],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06557357,"threshold_uncertainty_score":0.2193655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1125447253166468,"score_gpt":0.5824131139400014,"score_spread":0.4698683886233546,"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."}}