{"id":"W4235231084","doi":"10.1515/iupac.79.1009","title":"Chronic","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001381686,0.001427187,0.00155222,0.003993543,0.001198638,0.003908459,0.002254998,0.001884975,0.2812175],"category_scores_gemma":[0.01512286,0.0005302678,0.001839232,0.007741909,0.0003582257,0.003351701,0.00224513,0.00166384,0.2071215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001836958,"about_ca_system_score_gemma":0.00374388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02300343,"about_ca_topic_score_gemma":0.03730441,"domain_scores_codex":[0.9975068,0.0003743724,0.0004809334,0.0008655944,0.0004715243,0.0003008554],"domain_scores_gemma":[0.9929119,0.001928649,0.001040677,0.001449462,0.002245752,0.0004236914],"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":[0.0000933006,0.00001257537,0.001865807,0.001041039,0.00003535666,0.00001937389,0.00002332519,0.00006668014,0.00004251544,0.0008552409,0.9894522,0.006492498],"study_design_scores_gemma":[0.0001333073,0.00001565066,0.005572065,0.0008809274,0.00004621932,0.00007615206,0.0001154012,0.00009970669,0.00009773148,0.001493205,0.9914453,0.00002431008],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000123966,0.0001648484,0.00007901738,0.0001386907,0.00006140349,0.00002776748,0.9965509,0.0001339844,0.002719334],"genre_scores_gemma":[0.0007228753,0.0002635937,0.0003679826,0.0004029168,0.00005483712,0.0002456045,0.9937291,0.0001012236,0.004111962],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7187825,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501026313091362,"score_gpt":0.417972821985686,"score_spread":0.4029625588547724,"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."}}