{"id":"W4200056619","doi":"10.1177/00914150211065408","title":"Physical Health of Older Canadians: Do Intersections Between Immigrant and Refugee Status, Racialized Status, and Socioeconomic Position Matter?","year":2021,"lang":"en","type":"article","venue":"The International Journal of Aging and Human Development","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Toronto Metropolitan University; University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Immigration; Acculturation; Socioeconomic status; Odds; Health equity; Gerontology; Disadvantage; Demography; Psychology; Medicine; Sociology; Geography; Public health; Logistic regression; Population; Political science","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":[0.0003155817,0.00008355396,0.0001946927,0.0001311233,0.0001888472,0.00005881809,0.00006778056,0.00002335002,0.0001364801],"category_scores_gemma":[0.000004532798,0.00006845505,0.00002953727,0.00002343287,0.00006676083,0.00007569428,0.0000289516,0.0001586652,0.000002658758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001616677,"about_ca_system_score_gemma":0.0002715776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003103557,"about_ca_topic_score_gemma":0.004336637,"domain_scores_codex":[0.9990544,0.00009027893,0.0004324301,0.0001199781,0.0001360811,0.0001668763],"domain_scores_gemma":[0.9992876,0.00007244317,0.0003049106,0.00005708367,0.0001355956,0.0001423669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001306405,0.0001867005,0.6194704,0.0001113878,0.001217574,0.00002280961,0.3185315,0.000004755546,0.0002198978,0.009511922,0.004657484,0.04593497],"study_design_scores_gemma":[0.001205779,0.00007008975,0.9883471,0.0001265946,0.00002348745,0.0001081381,0.005549379,0.000001987867,0.0001174853,0.001259003,0.003116265,0.00007469464],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947659,0.001007539,0.00009919654,0.003730024,0.0002052859,0.00006338509,0.00001964346,0.000003224808,0.000105741],"genre_scores_gemma":[0.9986054,0.0001835235,0.0002076164,0.0006287746,0.0001674528,0.000003075124,0.00002417879,0.000007364108,0.0001726155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3688767,"threshold_uncertainty_score":0.4691671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01520467183803064,"score_gpt":0.3300479604427951,"score_spread":0.3148432886047644,"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."}}