{"id":"W3093648628","doi":"10.1080/02255189.2020.1824894","title":"COVID-19 and the gendered markets of people and products: explaining inequalities in infections and deaths","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Development Studies/Revue canadienne d études du développement","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Wellcome Trust; Wellcome; Bill and Melinda Gates Foundation","keywords":"Inequality; Coronavirus disease 2019 (COVID-19); Ethnic group; Blindness; Environmental health; Demographic economics; Disease; Development economics; Sociology; Medicine; Economics; Infectious disease (medical specialty); Optometry; Pathology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00261044,0.000252851,0.0003651788,0.001740567,0.002113759,0.002583891,0.0006520352,0.0007975434,0.00707175],"category_scores_gemma":[0.008464123,0.0001369633,0.0004765836,0.002416114,0.003472913,0.001446769,0.003144695,0.001322938,0.0002047219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006751065,"about_ca_system_score_gemma":0.006042685,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2528071,"about_ca_topic_score_gemma":0.2441242,"domain_scores_codex":[0.9981748,0.0007083442,0.00004486896,0.0001326556,0.000315687,0.0006237075],"domain_scores_gemma":[0.9959288,0.002033354,0.000838008,0.00015135,0.0003694449,0.0006790002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001432089,0.0001531092,0.542267,0.0001910225,0.00009980913,0.0003418804,0.01792137,0.0008762401,0.0001812758,0.3838508,0.006374542,0.04759973],"study_design_scores_gemma":[0.00003729262,0.0001733016,0.6719584,0.001300353,0.0001312705,0.0002504852,0.05018536,0.004369348,0.0002826204,0.1994965,0.07176138,0.00005373206],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8292245,0.009149923,0.002826483,0.05552144,0.0002267932,0.00005956092,0.001682203,0.00001667285,0.1012925],"genre_scores_gemma":[0.9965333,0.001186233,0.0003245094,0.0004551479,0.00003976209,0.00001535265,0.0001088743,0.000003926923,0.001332872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7471929,"threshold_uncertainty_score":0.5026712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1430083869422432,"score_gpt":0.3345443518055877,"score_spread":0.1915359648633445,"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."}}