{"id":"W4241009763","doi":"10.1515/iupac.79.1449","title":"Idiosyncrasy","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Linguistics and Cultural Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Linguistics; Philosophy; Biology; 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":[0.003309472,0.002358506,0.001937962,0.005209618,0.001476146,0.004638342,0.00368535,0.002164571,0.07851481],"category_scores_gemma":[0.0208363,0.0008606276,0.002969496,0.008573809,0.0009277769,0.003547341,0.003735587,0.002649073,0.1254534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001859495,"about_ca_system_score_gemma":0.002787194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01492049,"about_ca_topic_score_gemma":0.03485868,"domain_scores_codex":[0.9942882,0.001065849,0.001139113,0.001875855,0.001147188,0.0004838054],"domain_scores_gemma":[0.9927561,0.002305419,0.0005332013,0.002546461,0.001524451,0.0003345256],"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":[0.0001430831,0.00003459456,0.002819762,0.001058418,0.00007920041,0.00005449166,0.00006466616,0.0003354555,0.0001508779,0.001164208,0.9845266,0.009568494],"study_design_scores_gemma":[0.0001934672,0.00002232115,0.004187468,0.0004042941,0.0000500656,0.0002045551,0.0001282223,0.0006155698,0.000255492,0.002030466,0.9918711,0.00003705407],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007962117,0.0004904764,0.0005429109,0.0002562919,0.0001814917,0.00008975403,0.9928333,0.0009833019,0.003826362],"genre_scores_gemma":[0.0009784846,0.0001527831,0.0008534051,0.0002337864,0.00002220239,0.0002364851,0.9957694,0.0001823912,0.001571205],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07851481,"threshold_uncertainty_score":0.2626582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703466676095004,"score_gpt":0.3681106902036783,"score_spread":0.3410760234427282,"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."}}