{"id":"W4256095188","doi":"10.1515/iupac.76.0398","title":"Systemic","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; Toxicokinetics; Relation (database); Hazard; Toxicology; Computer science; Medicine; Chemistry; Pharmacology; Data mining; Biology; Linguistics; Philosophy","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":[0.001542566,0.002104688,0.001445477,0.003928876,0.001092285,0.003849279,0.002783836,0.001942502,0.1807882],"category_scores_gemma":[0.01052446,0.0007538311,0.001791533,0.006477667,0.0004085733,0.003406241,0.00293516,0.001865386,0.256443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001666159,"about_ca_system_score_gemma":0.002949737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01523335,"about_ca_topic_score_gemma":0.03196425,"domain_scores_codex":[0.9975152,0.0004479617,0.0003656195,0.0009099492,0.0005252192,0.0002360518],"domain_scores_gemma":[0.9954046,0.001221358,0.0004792746,0.001377399,0.001225555,0.0002918489],"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":[0.00005791258,0.00001350486,0.0007034889,0.0006363532,0.00002221074,0.00001416652,0.00002514673,0.0001357929,0.00008214577,0.0007969487,0.9923757,0.005136493],"study_design_scores_gemma":[0.00007593448,0.00001123628,0.001782629,0.0003816999,0.00001927865,0.00004642402,0.00006757495,0.0002210177,0.0001476746,0.001603898,0.9956227,0.00002003596],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001039122,0.0001237394,0.0001604494,0.000109811,0.00003759148,0.00002002773,0.9967352,0.0006166366,0.002092634],"genre_scores_gemma":[0.0002938267,0.000102566,0.0004302156,0.0001269545,0.00001126806,0.00009287292,0.997368,0.0001360502,0.001438325],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8192118,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530919668744106,"score_gpt":0.4113473955741205,"score_spread":0.3960381988866794,"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."}}