{"id":"W2074647149","doi":"10.1080/13557858.2013.848843","title":"Racialized and gendered disparities in occupational exposures among Chinese and white workers in Toronto","year":2013,"lang":"en","type":"article","venue":"Ethnicity and Health","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Social Sciences and Humanities Research Council of Canada; Workplace Safety and Insurance Board; Lupina Foundation","keywords":"Confounding; Poisson regression; Demography; Medicine; Population; Gerontology; Environmental health; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003949465,0.0002082954,0.0001950977,0.0006736658,0.001254879,0.0005055452,0.0003316278,0.0001674013,0.001592379],"category_scores_gemma":[0.001046584,0.000160366,0.0002533032,0.001253949,0.000478248,0.0001896673,0.0007658814,0.0002212009,0.00008161702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006083923,"about_ca_system_score_gemma":0.006532946,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9415694,"about_ca_topic_score_gemma":0.9704576,"domain_scores_codex":[0.9996531,0.00003849832,0.00001748288,0.00005176658,0.00008820619,0.0001508828],"domain_scores_gemma":[0.9994261,0.00005718044,0.0002024632,0.00002450558,0.000102696,0.0001870913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004090861,0.000009922664,0.9964471,0.00001099705,0.0000219907,0.00005415057,0.001588427,0.00006284602,0.0001947208,0.0001058292,0.0001475352,0.001315528],"study_design_scores_gemma":[0.000002168782,0.000009350798,0.9981694,0.000008195879,0.000009625282,0.00001656047,0.001475482,0.0001022594,0.00004377249,0.00001962156,0.000141071,0.000002435313],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991575,0.00009007003,0.00002332517,0.00005451745,0.000001636765,0.000003437505,0.0002426238,8.246786e-7,0.0004259566],"genre_scores_gemma":[0.9995762,0.00006468356,0.00002043448,0.00001073015,9.946548e-7,0.000002233884,0.0001336828,4.584224e-7,0.0001908036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05843055,"threshold_uncertainty_score":0.1175493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07682322877339624,"score_gpt":0.4426198911681568,"score_spread":0.3657966623947605,"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."}}