{"id":"W4234036154","doi":"10.1515/iupac.76.0394","title":"Subchronic Effect","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Nonlinear Dynamics and Pattern Formation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Hazard; Relation (database); Computer science; Toxicology; 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":[],"consensus_categories":[],"category_scores_codex":[0.0006730292,0.001848268,0.001332185,0.003079838,0.0009890019,0.002271538,0.001916813,0.001404917,0.1102177],"category_scores_gemma":[0.005443905,0.000448225,0.002049142,0.003483098,0.0004002158,0.001837059,0.001678493,0.001458527,0.09365723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135247,"about_ca_system_score_gemma":0.001553472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01513262,"about_ca_topic_score_gemma":0.03265033,"domain_scores_codex":[0.9986559,0.000138113,0.0002243706,0.0005280116,0.000311033,0.0001425016],"domain_scores_gemma":[0.997986,0.0006079421,0.000239993,0.0005321354,0.0004950682,0.0001389456],"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":[0.0003344626,0.00007535057,0.006208614,0.00229848,0.0001042083,0.00008986088,0.00006133744,0.0006185523,0.0008423502,0.001938884,0.9582909,0.02913709],"study_design_scores_gemma":[0.0001424203,0.00005482975,0.0147868,0.0004866092,0.0000977624,0.0002295652,0.000118292,0.0005632408,0.0009374161,0.002334505,0.9801999,0.00004871146],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001345731,0.001029568,0.0006381003,0.0001087973,0.0001453817,0.00006851032,0.9891583,0.0008040399,0.006701646],"genre_scores_gemma":[0.003159423,0.0004949817,0.001250879,0.0002310597,0.00003651456,0.0002045871,0.9882751,0.0002186445,0.006128869],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1102177,"threshold_uncertainty_score":0.3687151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007132649194800201,"score_gpt":0.3602707482243929,"score_spread":0.3531380990295926,"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."}}