{"id":"W3132800520","doi":"10.1016/j.socscimed.2021.113773","title":"Geographic access to COVID-19 healthcare in Brazil using a balanced float catchment area approach","year":2021,"lang":"en","type":"article","venue":"Social Science & Medicine","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":139,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Catchment area; Health care; Pandemic; Geography; Population; Inequality; Unit (ring theory); Business; Economic growth; Coronavirus disease 2019 (COVID-19); Environmental health; Medicine; Drainage basin; Economics; Cartography","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":[0.001471732,0.0003473789,0.0005725918,0.00296472,0.0008038469,0.001373127,0.0008273977,0.0004243956,0.002493443],"category_scores_gemma":[0.01069882,0.000317464,0.001116679,0.004411491,0.0006167952,0.001061746,0.002152772,0.0004501049,0.0002128291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003111106,"about_ca_system_score_gemma":0.003495022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3384071,"about_ca_topic_score_gemma":0.3693307,"domain_scores_codex":[0.9980561,0.0008781564,0.0001533476,0.0003187328,0.000270225,0.000323541],"domain_scores_gemma":[0.9979597,0.0007565867,0.0004822132,0.0001511978,0.0004293196,0.0002210235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006414321,0.000174671,0.9708291,0.000189725,0.0001964387,0.0001650717,0.003392354,0.001297891,0.0001472327,0.004557886,0.001118393,0.01786711],"study_design_scores_gemma":[0.00002266317,0.0001869724,0.9708797,0.0002721336,0.0002251652,0.0003330888,0.0132523,0.00952254,0.0001260407,0.001636281,0.003508358,0.00003485051],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904416,0.0004262849,0.00166181,0.00053357,0.00001277562,0.0002228502,0.002410772,0.00002284679,0.004267622],"genre_scores_gemma":[0.9972711,0.0001803045,0.00149246,0.00003090067,0.00000557464,0.0001164306,0.0006024796,0.000006363458,0.000294399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3384071,"threshold_uncertainty_score":0.6728746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09658827842592481,"score_gpt":0.4312457180551016,"score_spread":0.3346574396291768,"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."}}