{"id":"W4312180180","doi":"10.1093/ofid/ofac690","title":"Which Curve Are We Flattening? The Disproportionate Impact of COVID-19 Among Economically Marginalized Communities in Ontario, Canada, Was Unchanged From Wild-Type to Omicron","year":2022,"lang":"en","type":"article","venue":"Open Forum Infectious Diseases","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Public Health Ontario; University of Toronto; Sunnybrook Health Science Centre; St. Michael's Hospital","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Equity (law); Medicine; Demographic economics; Inequality; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Magnitude (astronomy); Demography; Public health; Socioeconomics; Virology; Economics; Political science; Sociology; Pathology","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006801069,0.0001799714,0.0004390611,0.00009338414,0.001875635,0.0002033258,0.0008457656,0.00004601632,0.007944016],"category_scores_gemma":[0.000362054,0.0001528618,0.0001131076,0.0003720252,0.0001621046,0.0002686459,0.0006618865,0.0003077057,0.000003595987],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004826232,"about_ca_system_score_gemma":0.008896254,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9998077,"about_ca_topic_score_gemma":0.999975,"domain_scores_codex":[0.9976484,0.0008004424,0.0004281233,0.0002305413,0.0003209314,0.0005715237],"domain_scores_gemma":[0.9981278,0.0006375475,0.0003106364,0.0003592056,0.000100386,0.000464422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002148688,0.00009795435,0.957799,0.00001611803,0.00006452196,0.000005207314,0.007272807,0.003105598,3.500785e-7,0.0008363671,0.03051993,0.00006729914],"study_design_scores_gemma":[0.0006531665,0.00009042745,0.898685,0.00003629416,0.00002944859,5.083863e-7,0.03108915,0.00003980167,5.088393e-7,0.001685546,0.06749273,0.0001974331],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9756047,0.0002095924,0.000002986345,0.01915923,0.0004136192,0.001136976,0.0008636197,0.00002562561,0.002583681],"genre_scores_gemma":[0.9937605,0.00007601191,0.000005091059,0.004817208,0.0000289458,0.000249541,0.0002323913,0.00001932229,0.0008109952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.059114,"threshold_uncertainty_score":0.9994238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03584593173254643,"score_gpt":0.3264278544006134,"score_spread":0.290581922668067,"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."}}