{"id":"W4250358054","doi":"10.1515/iupac.88.0737","title":"Endocardium","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Academic Writing and Publishing","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Data mining; Philosophy","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":[0.001719028,0.001240301,0.001531478,0.004848022,0.0008659274,0.003966885,0.002039274,0.001637607,0.1761896],"category_scores_gemma":[0.02095554,0.0006097845,0.001531871,0.006980557,0.0004599329,0.002427934,0.002537858,0.002061796,0.1760188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414827,"about_ca_system_score_gemma":0.003606455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01051784,"about_ca_topic_score_gemma":0.01605542,"domain_scores_codex":[0.9970927,0.0005650524,0.0007891282,0.0007589486,0.0005399446,0.0002540838],"domain_scores_gemma":[0.992393,0.002509859,0.001219175,0.001681261,0.001782478,0.0004141901],"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":[0.0001186872,0.00001070386,0.001438399,0.002366112,0.00003866781,0.00003706163,0.00003607211,0.00009530754,0.00007697848,0.00131083,0.982932,0.01153917],"study_design_scores_gemma":[0.0001013544,0.00001060119,0.002724547,0.001933795,0.00003853228,0.0001142064,0.0000734581,0.00009409619,0.0001152364,0.001482803,0.9932932,0.00001828384],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002211083,0.0007676879,0.0002348659,0.0003246968,0.0001804226,0.00006074179,0.9917194,0.0003745358,0.006116524],"genre_scores_gemma":[0.001128647,0.0009726891,0.0008372199,0.0005719879,0.00009612721,0.0003016479,0.9916038,0.000197981,0.00428985],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1761896,"threshold_uncertainty_score":0.5894129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03466683891543475,"score_gpt":0.4061706795286917,"score_spread":0.3715038406132569,"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."}}