{"id":"W4236290129","doi":"10.1515/iupac.79.2062","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; Chemical nomenclature; Computer science; Hazard; 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":[],"consensus_categories":[],"category_scores_codex":[0.001109411,0.00187407,0.001699605,0.002869755,0.001224239,0.002881715,0.002417893,0.001557981,0.1069898],"category_scores_gemma":[0.008400084,0.000430568,0.002813749,0.003639831,0.0004594237,0.002029732,0.001964258,0.001669078,0.0941212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001369622,"about_ca_system_score_gemma":0.002430424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02141897,"about_ca_topic_score_gemma":0.04162792,"domain_scores_codex":[0.9979068,0.0002416576,0.000324908,0.0008078081,0.0004349376,0.0002838967],"domain_scores_gemma":[0.9973994,0.0006321622,0.000228752,0.0008365517,0.0007121201,0.0001910159],"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":[0.0007655246,0.0001096042,0.01389024,0.001974385,0.0002520264,0.0001185256,0.00006105527,0.0008527471,0.0006157,0.002553314,0.9414495,0.03735736],"study_design_scores_gemma":[0.0003466152,0.0001006903,0.0213372,0.0005363388,0.000274293,0.0003606384,0.0001775999,0.0008420735,0.001016675,0.003372202,0.971576,0.00005960083],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002567794,0.001159737,0.0007286816,0.000198753,0.0002543918,0.000127818,0.9841111,0.0007523075,0.01009947],"genre_scores_gemma":[0.005513948,0.0004677793,0.001033725,0.0004172053,0.0000615149,0.0002376842,0.9845396,0.0001714899,0.007557031],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1069898,"threshold_uncertainty_score":0.3579164,"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."}}