{"id":"W2586522675","doi":"10.1111/dme.13326","title":"Impact of neighbourhood‐level inequity on paediatric diabetes care","year":2017,"lang":"en","type":"article","venue":"Diabetic Medicine","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"National Eye Institute; Hospital for Sick Children; American Diabetes Association","keywords":"Medicine; Neighbourhood (mathematics); Diabetes mellitus; Equity (law); Demography; Type 2 diabetes; Population; Regression analysis; Health equity; Environmental health; Public health; Endocrinology; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001199751,0.0001139718,0.0002056639,0.0004285318,0.00035288,0.0006937311,0.0003345961,0.0001981897,0.002141511],"category_scores_gemma":[0.00630328,0.0000912959,0.0002774039,0.000617509,0.000394037,0.0005497882,0.001600598,0.0003904056,0.00006940757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000876674,"about_ca_system_score_gemma":0.000886798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0215916,"about_ca_topic_score_gemma":0.03555929,"domain_scores_codex":[0.9985725,0.0007082609,0.00006743622,0.0001489109,0.000273728,0.0002291707],"domain_scores_gemma":[0.9975631,0.0008417941,0.0008545096,0.0001288885,0.0002900269,0.0003216575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004999995,0.0000264248,0.9869046,0.00004407072,0.00007292371,0.00008824662,0.0004919814,0.0004412049,0.00007125428,0.0008547957,0.0001713066,0.01078331],"study_design_scores_gemma":[0.000001642348,0.00003137703,0.9970375,0.00005707742,0.00002225676,0.0001130949,0.0009476222,0.0008376178,0.00005416002,0.0004068193,0.0004867486,0.000004055275],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994339,0.001146883,0.000485277,0.0004640705,0.00001550643,0.000008631944,0.0002528194,0.000003014326,0.003284712],"genre_scores_gemma":[0.9997194,0.0001095754,0.00007869204,0.00001103592,0.000005073779,0.000002604204,0.00003207996,5.622487e-7,0.0000408435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0215916,"threshold_uncertainty_score":0.04293185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09021362934972037,"score_gpt":0.4480241074102331,"score_spread":0.3578104780605127,"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."}}