{"id":"W3033761009","doi":"10.1136/bmj.m2149","title":"Using socioeconomics to counter health disparities arising from the covid-19 pandemic","year":2020,"lang":"en","type":"article","venue":"BMJ","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario College of Art and Design; Institute for Work & Health; University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Socioeconomic status; Work (physics); Health equity; Environmental health; Medicine; Economic growth; Health care; Virology; Economics; Outbreak; Population; Engineering; Infectious disease (medical specialty); Disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0265435,0.001175617,0.001044981,0.00418959,0.003127245,0.006052198,0.002433368,0.006786498,0.008060078],"category_scores_gemma":[0.09787866,0.0003607412,0.001761239,0.001935486,0.00653693,0.006848268,0.006869843,0.01159524,0.001892366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003898461,"about_ca_system_score_gemma":0.01118508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01952027,"about_ca_topic_score_gemma":0.03781795,"domain_scores_codex":[0.9887626,0.007068563,0.0004687582,0.0005852464,0.002181371,0.0009334202],"domain_scores_gemma":[0.9469275,0.03611343,0.003608095,0.00227026,0.007014527,0.004066234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000262937,0.0005942716,0.05528914,0.001899568,0.001064012,0.0001845946,0.007594499,0.001273476,0.0002967929,0.1445579,0.4743375,0.3126454],"study_design_scores_gemma":[0.0003552136,0.0004533781,0.05406244,0.00837831,0.0009672698,0.0001676429,0.01666392,0.002397881,0.001208699,0.33629,0.5787815,0.0002736833],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.004286365,0.008675375,0.00500524,0.9531409,0.01148838,0.0001021273,0.0003897388,0.00009164018,0.01682024],"genre_scores_gemma":[0.2792256,0.02509114,0.02901317,0.6257581,0.02867073,0.0009166389,0.0004332501,0.0002137129,0.01067763],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0265435,"threshold_uncertainty_score":0.1403771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3006296197333063,"score_gpt":0.4741479358345387,"score_spread":0.1735183161012325,"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."}}