{"id":"W4324137922","doi":"10.1136/oem-2023-epicoh.34","title":"O-176 Development of a silica job-exposure-matrix for mining using historical exposure measurements in Ontario, Canada","year":2023,"lang":"en","type":"article","venue":"Abstracts","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; Occupational Cancer Research Centre; Public Health Ontario; University of Toronto","funders":"","keywords":"Christian ministry; Job-exposure matrix; Environmental science; Exposure assessment; Mining industry; Occupational exposure; Mining engineering; Environmental health; Statistics; Geology; Mathematics; Medicine","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":[0.001886059,0.0001349394,0.0003199014,0.0001992222,0.0004843481,0.00000313619,0.0001659512,0.0001706541,0.0001213257],"category_scores_gemma":[0.000725793,0.0001344722,0.00003850571,0.000336796,0.00001117025,0.00007373538,0.00006144644,0.0004416862,0.00001937863],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.00549478,"about_ca_system_score_gemma":0.01893767,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8877847,"about_ca_topic_score_gemma":0.9934702,"domain_scores_codex":[0.9968759,0.0001294004,0.00115426,0.0002588846,0.000785836,0.0007957593],"domain_scores_gemma":[0.9979191,0.001042165,0.0002544154,0.0001834544,0.0003363642,0.0002645172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003072068,0.00006402204,0.985337,0.0005817969,0.00002115681,0.000009315307,0.003528313,0.0006125184,0.0009202865,0.00001081986,0.00615277,0.002454861],"study_design_scores_gemma":[0.001030537,0.00006201492,0.9728001,0.0002343327,0.000004700663,4.172197e-7,0.0004957843,0.0000818128,0.0000919532,0.00002189043,0.02505819,0.000118219],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996283,0.00008925088,0.00001789317,0.0004011102,0.0007821707,0.001057398,0.00001478961,0.00002301011,0.001331387],"genre_scores_gemma":[0.993984,0.000002776499,0.003742994,0.0001066502,0.00008385951,0.0002092473,0.0000496286,0.00002129109,0.001799504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1056855,"threshold_uncertainty_score":0.998323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2663029373959935,"score_gpt":0.4525705217547737,"score_spread":0.1862675843587802,"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."}}