{"id":"W4379383004","doi":"10.32920/23295992.v1","title":"Examining the Relationship Between Access to Healthcare and Marginalization in Toronto","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Health care; Ethnic group; Healthcare policy; Demographic economics; Demography; Geography; Sociology; Economic growth; Economics; Health policy; International health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003908385,0.0001515012,0.0001868328,0.001101005,0.001593416,0.001099213,0.0003908499,0.0001784318,0.002685369],"category_scores_gemma":[0.003227378,0.000121747,0.0003563506,0.002372382,0.00143904,0.000407208,0.001742198,0.000405277,0.00008350281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01263106,"about_ca_system_score_gemma":0.007566144,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9394158,"about_ca_topic_score_gemma":0.9621985,"domain_scores_codex":[0.999431,0.0001144479,0.00002657642,0.00005722529,0.0001373037,0.000233516],"domain_scores_gemma":[0.9978563,0.0004162806,0.0005787998,0.00009080394,0.0004071864,0.0006505865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007930503,0.00002447649,0.9762431,0.00005091909,0.00007035806,0.0002327679,0.01621701,0.0005793888,0.0002348792,0.001751789,0.0008187814,0.003697144],"study_design_scores_gemma":[0.000001686435,0.00001542321,0.9870977,0.0000186506,0.00001708844,0.00003029156,0.01134932,0.0003041248,0.00005901681,0.00008513517,0.001015897,0.000005732176],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969838,0.0001339338,0.00006053751,0.0002116508,0.00000242642,0.000006547897,0.0004085606,0.000002230429,0.00219027],"genre_scores_gemma":[0.9995639,0.00006205722,0.00002776503,0.000006881509,0.000001448949,0.000003371282,0.000108383,7.032413e-7,0.0002254974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06058425,"threshold_uncertainty_score":0.121882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5237014481800351,"score_gpt":0.578787617213204,"score_spread":0.05508616903316899,"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."}}