{"id":"W4255359396","doi":"10.1515/iupac.79.1059","title":"Congenital","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; Library science; 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":[0.001409796,0.001843412,0.001433271,0.003744259,0.001102798,0.003690465,0.00266538,0.001787301,0.210431],"category_scores_gemma":[0.01280299,0.00058119,0.00190616,0.006556374,0.0003657818,0.002753199,0.002282691,0.001767409,0.2607391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001717958,"about_ca_system_score_gemma":0.003029655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02155774,"about_ca_topic_score_gemma":0.03465739,"domain_scores_codex":[0.9974619,0.0003892092,0.0004091645,0.0009175041,0.0005319182,0.0002902814],"domain_scores_gemma":[0.9946252,0.001227156,0.0005250293,0.001429286,0.001863334,0.0003300114],"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":[0.000083507,0.00001384324,0.001282206,0.0006344813,0.00003084798,0.00001492387,0.00001817447,0.0000994189,0.00006186427,0.0006739949,0.9906731,0.006413606],"study_design_scores_gemma":[0.0001096017,0.00001471054,0.003311528,0.0004857527,0.00003335708,0.00006200971,0.00008165056,0.0001607368,0.0001543354,0.001407046,0.9941572,0.0000220093],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001068426,0.00009721364,0.0001008946,0.00009534218,0.00004477526,0.00002006035,0.9973069,0.0002444522,0.001983367],"genre_scores_gemma":[0.0003973848,0.0001017537,0.000314706,0.000168691,0.00001568044,0.0001009733,0.9969536,0.00008070395,0.001866476],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.789569,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0164155962784517,"score_gpt":0.4122104630801569,"score_spread":0.3957948668017052,"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."}}