{"id":"W4249283150","doi":"10.1515/iupac.87.0222","title":"Electrophysiology","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Cardiac electrophysiology and arrhythmias","field":"Medicine","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; Neuroscience; Chemistry; Linguistics; Philosophy; 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":[0.0009313271,0.001362009,0.001296698,0.00247097,0.000390393,0.001958435,0.001766762,0.001473963,0.06830712],"category_scores_gemma":[0.01014148,0.0003673653,0.001407631,0.003078244,0.0002623103,0.001218467,0.00147781,0.001361766,0.0694489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007714781,"about_ca_system_score_gemma":0.001483919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004175006,"about_ca_topic_score_gemma":0.008795432,"domain_scores_codex":[0.9989375,0.0001627859,0.000313337,0.0002992124,0.0002012696,0.00008589462],"domain_scores_gemma":[0.9950688,0.001494102,0.0009085758,0.001128794,0.0011419,0.0002579011],"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":[0.0004804686,0.00003611737,0.005662081,0.005287257,0.00018019,0.0001649255,0.00003425618,0.0005581932,0.0003558316,0.0009724559,0.9600232,0.02624502],"study_design_scores_gemma":[0.0005429768,0.00006432565,0.01972584,0.002735757,0.0001842702,0.0008263331,0.00006087722,0.0005646216,0.0006082618,0.002987878,0.9716378,0.00006109474],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004872404,0.000633729,0.000403382,0.0001239786,0.00006239831,0.00005508012,0.9944424,0.0005081427,0.003283621],"genre_scores_gemma":[0.001922768,0.0005846178,0.0008133258,0.0002400916,0.00004993453,0.0002409658,0.9940789,0.00008640314,0.001983022],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06830712,"threshold_uncertainty_score":0.2285101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008172691711022056,"score_gpt":0.3782572015624087,"score_spread":0.3700845098513866,"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."}}