{"id":"W4408638286","doi":"10.1016/j.lana.2025.101056","title":"Inequalities in paediatric hospitalisations for costly and prevalent conditions in Ontario, Canada: a population-based cohort study","year":2025,"lang":"en","type":"article","venue":"The Lancet Regional Health - Americas","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Hospital for Sick Children; Public Health Ontario; University of Toronto","funders":"Ministry of Long-Term Care; Canadian Institutes of Health Research; Physicians' Services Incorporated Foundation; Institute for Clinical Evaluative Sciences; Hospital for Sick Children; Centre Hospitalier pour Enfants de l'est de l'Ontario; Kementerian Kesihatan Malaysia; Immigration, Refugees and Citizenship Canada; Institut canadien d'information sur la santé; Ministry of Health, Ontario","keywords":"Cohort; Inequality; Medicine; Demography; Cohort study; Population; Pediatrics; Geography; Environmental health; Internal medicine; Mathematics; Sociology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001606212,0.0001645576,0.000580904,0.000274581,0.001189319,0.000009934105,0.0001755631,0.00007997055,0.00007589858],"category_scores_gemma":[0.0002662814,0.000144055,0.00003587534,0.0006012191,0.00007792242,0.0000758754,0.00005267347,0.0006917343,0.000002456525],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002288436,"about_ca_system_score_gemma":0.006697923,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9869469,"about_ca_topic_score_gemma":0.9984976,"domain_scores_codex":[0.996891,0.0009399516,0.0009409685,0.0003241747,0.0002881352,0.000615746],"domain_scores_gemma":[0.9967311,0.002335797,0.0003530591,0.0003347624,0.0001251563,0.0001201218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009885868,0.0001614018,0.9532437,0.0003307515,0.00001556928,9.888695e-7,0.005015624,0.0005796543,1.858519e-8,0.01955394,0.02093755,0.00006191281],"study_design_scores_gemma":[0.001822554,0.0001331427,0.9761846,0.0002263853,0.00002075896,2.666617e-7,0.006459152,0.0008015585,9.865212e-9,0.003014594,0.01122093,0.0001160397],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9284953,0.0004439877,0.00005373537,0.06396392,0.0004134939,0.005879677,0.0003048606,0.00003753633,0.0004074329],"genre_scores_gemma":[0.9784552,0.0001043557,0.0001957974,0.01743408,0.0001249568,0.002688646,0.0004574298,0.00001184036,0.0005277071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04995983,"threshold_uncertainty_score":0.9989332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1898894064193173,"score_gpt":0.456885062307068,"score_spread":0.2669956558877508,"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."}}