{"id":"W4231879722","doi":"10.1515/iupac.79.1030","title":"Cocarcinogen","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","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","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001587697,0.0005769178,0.0007108342,0.00008048335,0.000115936,0.00005484947,0.0007498486,0.0007985757,0.06081297],"category_scores_gemma":[0.0002667848,0.0004406715,0.0004623835,0.0001602612,0.000307905,0.0000508934,0.0002108971,0.0006671763,0.000009061325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002380459,"about_ca_system_score_gemma":0.0004574564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003184243,"about_ca_topic_score_gemma":0.00004039011,"domain_scores_codex":[0.9971195,0.00001523193,0.0005199005,0.0006656296,0.001110203,0.0005695671],"domain_scores_gemma":[0.9977784,0.0001067478,0.0002439974,0.00123144,0.0002944577,0.0003449599],"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":[0.00008341649,0.0001799195,0.00003486424,0.0006674439,0.0002541443,0.0001437515,0.000001899067,1.012581e-7,0.0005390325,0.000007237642,0.9976594,0.0004288058],"study_design_scores_gemma":[0.0006833636,0.00002535444,0.000002307535,0.0005155209,0.0002772086,0.00002893008,0.00001899007,0.00000158147,0.003544315,0.0002500827,0.9940606,0.0005916848],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002422176,0.0008168368,0.00002374695,0.0002049048,0.0001219817,0.00004214495,0.9961861,0.0001285366,0.002233564],"genre_scores_gemma":[0.0001744894,0.0006701512,0.00001105318,0.0001612666,0.001520867,0.00001097612,0.9955214,0.0000486637,0.001881129],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06080391,"threshold_uncertainty_score":0.9998045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01094530609100513,"score_gpt":0.3616213347135891,"score_spread":0.350676028622584,"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."}}