{"id":"W3128682187","doi":"10.1186/s12939-021-01399-1","title":"Sharpening our public health lens: advancing im/migrant health equity during COVID-19 and beyond","year":2021,"lang":"en","type":"letter","venue":"International Journal for Equity in Health","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; Simon Fraser University","funders":"Canadian Institutes of Health Research; National Institutes of Health; National Institute on Drug Abuse; Simon Fraser University; Michael Smith Health Research BC; Vancouver Foundation","keywords":"Public health; Coronavirus disease 2019 (COVID-19); Health equity; Equity (law); 2019-20 coronavirus outbreak; Sharpening; Social policy; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pandemic; Health policy; Public health policy; Political science; Lens (geology); Medicine; Virology; Nursing; Infectious disease (medical specialty); Optics; Outbreak; Law","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02818505,0.0009420903,0.001421073,0.001834244,0.01221644,0.01835338,0.005054526,0.03021362,0.01550973],"category_scores_gemma":[0.053101,0.0005542735,0.001915529,0.001345254,0.03386598,0.02501344,0.01524992,0.03739234,0.001644496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01474643,"about_ca_system_score_gemma":0.05630712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01691885,"about_ca_topic_score_gemma":0.02506304,"domain_scores_codex":[0.9757934,0.01577055,0.0008896938,0.001651397,0.001918492,0.003976489],"domain_scores_gemma":[0.9425783,0.04160931,0.003036309,0.001383615,0.004520834,0.006871634],"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":[0.0001549322,0.0001711227,0.002246341,0.004711851,0.00009658105,0.001910395,0.07698538,0.0004825427,0.0005529724,0.2888375,0.5272187,0.09663177],"study_design_scores_gemma":[0.00005158789,0.0001576169,0.002511267,0.0148915,0.0000846467,0.0007647254,0.0859973,0.0002887044,0.000351471,0.1298199,0.7649689,0.0001124754],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001078339,0.01436432,0.000439837,0.9708906,0.007940998,0.00002312818,0.00004232326,0.00001728997,0.005203133],"genre_scores_gemma":[0.08335156,0.03688208,0.001409172,0.8431081,0.03075386,0.0001993435,0.00007716029,0.00005985662,0.004158855],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03021362,"threshold_uncertainty_score":0.1490586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2112996519432553,"score_gpt":0.5074029245958318,"score_spread":0.2961032726525765,"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."}}