{"id":"W1974799565","doi":"10.1097/00001648-200611001-00142","title":"Substance Profiling for Categorization and Screening Health Risk Assessments of Existing Substances Under the Canadian Environmental Protection Act (CEPA)","year":2006,"lang":"en","type":"article","venue":"Epidemiology","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Categorization; Profiling (computer programming); Risk assessment; Risk analysis (engineering); Environmental health; Population; Hazard analysis; Computer science; Exposure assessment; Data science; Environmental planning; Business; Geography; Medicine; Engineering; Computer security; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00222074,0.0001320392,0.0002392094,0.00003560634,0.00055073,0.000007889529,0.0001230037,0.00009039555,0.00005101579],"category_scores_gemma":[0.0002242245,0.0001028544,0.00003293009,0.00012256,0.0002880517,0.0001446013,0.000022534,0.0001645129,0.000003455536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005781615,"about_ca_system_score_gemma":0.00005191998,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09334505,"about_ca_topic_score_gemma":0.2676286,"domain_scores_codex":[0.9982495,0.0004322673,0.000420755,0.0003144579,0.0001088526,0.0004741848],"domain_scores_gemma":[0.9987983,0.0004207269,0.0005113127,0.0001652872,0.000001401491,0.0001029551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003344104,0.00002362078,0.9191123,0.000009821996,0.00002149233,4.075067e-7,0.0001951145,0.005789924,0.005327916,0.0009822026,0.00009896819,0.06840475],"study_design_scores_gemma":[0.0002604653,0.0001163602,0.9780224,0.000009965652,0.00001131347,0.000009258032,0.0002042898,0.01278073,0.001411235,0.006582611,0.0004723271,0.0001190338],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8624835,0.0004814237,0.1338176,0.001498913,0.0001305199,0.0009208415,0.0001498007,0.00002530749,0.0004920465],"genre_scores_gemma":[0.9907879,0.00004745505,0.008733627,0.0002354356,0.00006304183,0.00002371533,0.00001344314,0.00001672186,0.00007863587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1742835,"threshold_uncertainty_score":0.9126924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0820784936221123,"score_gpt":0.3369438223785062,"score_spread":0.2548653287563939,"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."}}