{"id":"W4400355932","doi":"10.1093/occmed/kqae023.0216","title":"SS34-04 WHWB ADVOCACY ACTIVITIES FOR OLD AND EMERGING RISKS: COVID-19, ACCELERATED SILICOSIS FROM ARTIFICIAL STONE COUNTERTOPS, AND ASBESTOS EXPOSURE","year":2024,"lang":"en","type":"article","venue":"Occupational Medicine","topic":"Occupational and environmental lung diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Auto Workers","funders":"","keywords":"Silicosis; Asbestos; Coronavirus disease 2019 (COVID-19); Environmental health; Medicine; Asbestosis; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Occupational exposure; Virology; Metallurgy; Pathology; Outbreak; Materials science; Disease","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":[0.0001791603,0.0002493618,0.0003492598,0.0001778537,0.0002203936,0.00004300463,0.00004972465,0.00009749725,0.0008570098],"category_scores_gemma":[0.0003577716,0.0001989975,0.00005756342,0.0001546182,0.0003076173,0.0002234428,0.00004069315,0.0001195041,0.00001013034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001420901,"about_ca_system_score_gemma":0.0002168128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007775237,"about_ca_topic_score_gemma":0.00005900182,"domain_scores_codex":[0.9984222,0.00003445221,0.0003599687,0.0004961048,0.000475466,0.0002118034],"domain_scores_gemma":[0.9986296,0.0007328416,0.00007202842,0.0001485682,0.00004453208,0.0003724505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008456302,0.0007276403,0.8223095,0.001867554,0.0009986873,0.0001707833,0.00414296,0.0001450223,0.06006872,0.003900291,0.02619362,0.07101892],"study_design_scores_gemma":[0.00354174,0.001199139,0.9523757,0.0008509446,0.0009552784,0.0000663712,0.002152678,0.006509337,0.001379445,0.004123264,0.02641441,0.0004316844],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9837285,0.005959451,0.001430362,0.007100105,0.0003725957,0.000600238,0.0005869232,0.0001161134,0.0001056705],"genre_scores_gemma":[0.9924772,0.0005258967,0.0004591261,0.002871634,0.001026431,0.0001625228,0.002007971,0.00003404863,0.0004351707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1300662,"threshold_uncertainty_score":0.9383656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07449929740228813,"score_gpt":0.3747525276275142,"score_spread":0.3002532302252261,"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."}}