{"id":"W2312798270","doi":"10.1093/annhyg/mev092","title":"Trends in OSHA Compliance Monitoring Data 1979–2011: Statistical Modeling of Ancillary Information across 77 Chemicals","year":2016,"lang":"en","type":"article","venue":"The Annals of Occupational Hygiene","topic":"Occupational and environmental lung diseases","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail; Université de Montréal","funders":"","keywords":"Context (archaeology); Confidence interval; Environmental health; Logistic regression; Occupational exposure limit; Occupational exposure; Odds ratio; Environmental science; Statistics; Medicine; Mathematics; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.0003270153,0.0001036713,0.0002096096,0.0000761906,0.00004111822,0.000005313785,0.0002360122,0.00004177205,0.0001561933],"category_scores_gemma":[0.000185982,0.00006415465,0.00004640075,0.0001366447,0.0001539264,0.0004623971,0.0001651375,0.00005722342,0.00003299727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002902418,"about_ca_system_score_gemma":0.0000502495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007778887,"about_ca_topic_score_gemma":0.000002460851,"domain_scores_codex":[0.9986641,0.00002313795,0.0004834344,0.0001492823,0.0004956311,0.0001844081],"domain_scores_gemma":[0.9990589,0.0001736383,0.0001548749,0.0004039374,0.0001372332,0.00007143849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004274333,0.0005979464,0.8782485,0.0002429939,0.0001045285,0.000003669596,0.0002692498,0.003497824,0.009064457,0.0008960346,0.002239004,0.1005615],"study_design_scores_gemma":[0.0006930284,0.00007398371,0.9800846,0.000255079,0.00001761494,0.000003816735,0.00004880836,0.01396601,0.004081749,0.000418974,0.0002699078,0.00008641273],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936854,0.0002578809,0.002312144,0.0008958636,0.00004621433,0.0001005233,0.002382028,0.00001063967,0.0003093356],"genre_scores_gemma":[0.9977787,0.0001322768,0.001011473,0.0001281438,0.00007445353,0.000008105801,0.0008060911,0.000006217671,0.00005451747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1018361,"threshold_uncertainty_score":0.2616151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2496331972427416,"score_gpt":0.4342928235650596,"score_spread":0.184659626322318,"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."}}