{"id":"W4251706227","doi":"10.1515/iupac.79.2113","title":"Threshold","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":[0.001511261,0.002055332,0.001605971,0.004174696,0.001227122,0.004649451,0.003203569,0.002041526,0.1893307],"category_scores_gemma":[0.01720478,0.0006446243,0.002301694,0.006160532,0.0004328584,0.003462318,0.00243946,0.002120898,0.2237723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001861116,"about_ca_system_score_gemma":0.003356111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01983203,"about_ca_topic_score_gemma":0.04102029,"domain_scores_codex":[0.9973895,0.0003876615,0.0004418565,0.0009764424,0.0004974981,0.0003070743],"domain_scores_gemma":[0.9948489,0.001560148,0.0004352672,0.001333141,0.001547964,0.0002746732],"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":[0.0001019067,0.00001903991,0.00149344,0.0009736014,0.00004312046,0.00002257564,0.00003217486,0.0002304543,0.00007467307,0.001172417,0.986564,0.009272631],"study_design_scores_gemma":[0.0001378584,0.00002007591,0.003003655,0.000633075,0.00005362921,0.00008427482,0.0001225331,0.0004193374,0.0002201244,0.004329547,0.9909436,0.00003236762],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001857412,0.0001696413,0.000230039,0.0001528087,0.00007067643,0.00004040177,0.9956185,0.0004947758,0.003037468],"genre_scores_gemma":[0.0007296562,0.0001497187,0.0007837675,0.0002056958,0.00002118931,0.0001897922,0.9954135,0.0001562612,0.002350537],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8106693,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0204179899693156,"score_gpt":0.4171378161450166,"score_spread":0.396719826175701,"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."}}