{"id":"W4239891261","doi":"10.1515/iupac.79.1646","title":"Mordant","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; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001467325,0.001896448,0.001814725,0.003752854,0.001106184,0.004166191,0.002838942,0.001722402,0.1586308],"category_scores_gemma":[0.01076442,0.0006852911,0.002160219,0.006426203,0.0004501628,0.002235277,0.002707374,0.00203356,0.2306866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001476863,"about_ca_system_score_gemma":0.002848959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01687188,"about_ca_topic_score_gemma":0.03571452,"domain_scores_codex":[0.998149,0.0003763082,0.0002599685,0.0006162523,0.0003752635,0.0002231224],"domain_scores_gemma":[0.996491,0.0009627449,0.0004189458,0.0009930864,0.0008271673,0.0003070757],"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":[0.00009542461,0.00001247231,0.0008696796,0.0008218835,0.00003808826,0.00001637403,0.00002301927,0.0001742781,0.00006209552,0.0006942788,0.9923027,0.004889613],"study_design_scores_gemma":[0.0001507201,0.00001661645,0.001943971,0.0004970661,0.00003569281,0.00004909587,0.000051786,0.0002408243,0.0001472238,0.001484103,0.9953609,0.00002207709],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009430574,0.0001359844,0.0001003731,0.00009561121,0.00003788964,0.00001552874,0.9977643,0.0003944379,0.001361454],"genre_scores_gemma":[0.0003429372,0.000139757,0.0003864658,0.0001184149,0.00001501138,0.00009926919,0.9974179,0.0001455556,0.001334751],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8413692,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01677440193451566,"score_gpt":0.4245399349211204,"score_spread":0.4077655329866047,"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."}}