{"id":"W4239989739","doi":"10.1515/iupac.79.1094","title":"Cumulative Incidence Rate","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemical Safety and Risk Management","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Hazard; 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":[0.0004632887,0.0005112766,0.0006350282,0.0001058729,0.00008125611,0.00003306406,0.000630366,0.0004267151,0.004915143],"category_scores_gemma":[0.0009841137,0.0003678226,0.0002211165,0.0002154489,0.0001264533,0.0001097286,0.0004984537,0.0007238996,0.00001980967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006839055,"about_ca_system_score_gemma":0.0001453852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001569148,"about_ca_topic_score_gemma":0.0001329246,"domain_scores_codex":[0.9973898,0.00004867659,0.0005636073,0.0006076742,0.0008570441,0.0005331758],"domain_scores_gemma":[0.9982175,0.0002867423,0.0002329979,0.0007969739,0.0002418548,0.0002239051],"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":[0.0001356271,0.00009246948,7.500951e-7,0.0002114755,0.0001384389,0.00006727404,0.00000809353,0.0001035731,0.0004100083,0.00005998371,0.9969779,0.00179447],"study_design_scores_gemma":[0.000716817,0.00004308116,0.000006204544,0.0006734169,0.0001149124,0.000002803816,0.000006921719,0.0003005569,0.0007717488,0.0004355814,0.996375,0.0005529845],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006487448,0.0004110552,0.002317326,0.0006330214,0.000451559,0.0002422939,0.9955747,0.0001544033,0.0001507314],"genre_scores_gemma":[0.00007923642,0.001383628,0.00006399003,0.0002920654,0.0009769284,0.00001864258,0.9955394,0.00004767041,0.001598382],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.004895333,"threshold_uncertainty_score":0.9998774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01294233124430518,"score_gpt":0.3694635031033686,"score_spread":0.3565211718590635,"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."}}