{"id":"W2613543905","doi":"10.1016/j.annepidem.2017.05.010","title":"Addressing refugee health through evidence-based policies: a case study","year":2017,"lang":"en","type":"article","venue":"Annals of Epidemiology","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bruyère; University of Ottawa","funders":"National Heart, Lung, and Blood Institute; Centers for Disease Control and Prevention; National Center for Chronic Disease Prevention and Health Promotion; University of California, San Francisco; U.S. Department of Health and Human Services","keywords":"Refugee; Medicine; Health policy; Multidisciplinary approach; Global health; Public relations; Epidemiology; Health services research; Public health; Economic growth; Environmental health; Political science; Nursing","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":[0.006940489,0.0005964246,0.0006107873,0.001890066,0.009654054,0.003937705,0.001573408,0.005484721,0.005880235],"category_scores_gemma":[0.01737766,0.000498272,0.0007184141,0.002078638,0.003927927,0.002953386,0.005388476,0.004316749,0.0004713943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004344469,"about_ca_system_score_gemma":0.007171941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01052828,"about_ca_topic_score_gemma":0.02543403,"domain_scores_codex":[0.9948716,0.003157454,0.000250855,0.0001686284,0.0003611559,0.0011904],"domain_scores_gemma":[0.9888914,0.006005635,0.001428447,0.0006521505,0.0008881071,0.002134312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"case_report","study_design_scores_codex":[0.0009355,0.01344169,0.177372,0.001891001,0.0003089027,0.35187,0.2704188,0.001437756,0.001741051,0.06344128,0.0197033,0.09743872],"study_design_scores_gemma":[0.0003369728,0.001822356,0.02564312,0.002880322,0.0001926394,0.09642339,0.8136263,0.001423043,0.001018686,0.006404241,0.05008909,0.000139914],"study_design_candidate":"case_report","study_design_consensus":"case_report","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9615769,0.001360185,0.001330258,0.01930355,0.0001758241,0.0003800064,0.0001239588,0.00001420677,0.01573525],"genre_scores_gemma":[0.9901248,0.002354227,0.001918718,0.00230529,0.00005756276,0.0002216044,0.00004289442,0.0000133795,0.002961388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01052828,"threshold_uncertainty_score":0.03670526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7308087089121699,"score_gpt":0.6182885239558085,"score_spread":0.1125201849563614,"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."}}