{"id":"W4242778155","doi":"10.1515/iupac.87.0395","title":"Muscarinic","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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; Organic chemistry; Data mining","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":[0.0008547084,0.001595949,0.001775987,0.003370209,0.0006481956,0.002160179,0.002390767,0.001850212,0.07807669],"category_scores_gemma":[0.00694968,0.0005886722,0.001781003,0.005300434,0.0003222921,0.001811666,0.001436664,0.001833003,0.06837703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001328634,"about_ca_system_score_gemma":0.002054768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01459276,"about_ca_topic_score_gemma":0.02951996,"domain_scores_codex":[0.9988652,0.0001469115,0.00030714,0.0003397675,0.000221494,0.0001194775],"domain_scores_gemma":[0.9974928,0.0006715001,0.0006598698,0.0005033262,0.0005361586,0.000136419],"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":[0.0009455347,0.00005759865,0.004889879,0.008468095,0.0002250491,0.0001128181,0.00004392894,0.0003956327,0.0006466409,0.001192973,0.9556274,0.02739434],"study_design_scores_gemma":[0.0005123711,0.00008614834,0.01827233,0.001857555,0.0002682212,0.0003616757,0.00006362439,0.000253304,0.0006581875,0.002316565,0.9752936,0.00005649013],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004719028,0.001175031,0.0001309155,0.0001508921,0.00004883705,0.00003999134,0.9952779,0.0001828701,0.002521738],"genre_scores_gemma":[0.001665903,0.001077538,0.0006087259,0.0002815234,0.00002405173,0.0002135533,0.9936516,0.0000617131,0.002415398],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07807669,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01842048308831296,"score_gpt":0.4287913498027893,"score_spread":0.4103708667144764,"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."}}