{"id":"W4246175003","doi":"10.1515/iupac.79.1079","title":"Criterion","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":[0.003261674,0.001985553,0.00217919,0.005528924,0.001566502,0.005741382,0.00385953,0.002907524,0.2061599],"category_scores_gemma":[0.03733282,0.0005693687,0.002342656,0.008298568,0.0007200279,0.003990629,0.002702354,0.002310557,0.1942255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002495954,"about_ca_system_score_gemma":0.0056073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01984097,"about_ca_topic_score_gemma":0.02766133,"domain_scores_codex":[0.9942694,0.0009616714,0.001171401,0.001725755,0.001267221,0.0006045856],"domain_scores_gemma":[0.9869967,0.003915897,0.00121909,0.002530846,0.004744657,0.0005929603],"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":[0.0001970852,0.00003990202,0.003858919,0.001554626,0.00007151887,0.00004310567,0.00005480175,0.0002097625,0.00007587898,0.002085035,0.9790792,0.01273009],"study_design_scores_gemma":[0.0003064685,0.0000341085,0.006373678,0.001209993,0.00008225471,0.0001304095,0.0002598049,0.0003517393,0.0001817567,0.005187799,0.9858393,0.00004275758],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005685014,0.0003760282,0.0004758626,0.0003424107,0.0001410778,0.0002008247,0.9900672,0.0003110413,0.007516971],"genre_scores_gemma":[0.002079515,0.0002553657,0.001214808,0.0005383587,0.0000671032,0.0009432563,0.9891991,0.0001713292,0.005531201],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7938401,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0180888195020821,"score_gpt":0.4372729558533304,"score_spread":0.4191841363512483,"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."}}