{"id":"W2583647507","doi":"10.3390/ijerph14020144","title":"Building Responsive Health Systems to Help Communities Affected by Migration: An International Delphi Consensus","year":2017,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bruyère; University of Ottawa","funders":"","keywords":"Disadvantaged; Delphi method; Health equity; Health policy; Delphi; Equity (law); Economic growth; Political science; Environmental health; Medicine; Health care; Economics; Computer science","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":[0.1488971,0.001154084,0.0007586173,0.003418855,0.008101857,0.005520396,0.003003221,0.003735313,0.003681983],"category_scores_gemma":[0.06383724,0.0009466165,0.001223089,0.00201833,0.006535654,0.00607887,0.01864148,0.004980911,0.0005253622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01162322,"about_ca_system_score_gemma":0.03947105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004240027,"about_ca_topic_score_gemma":0.004154841,"domain_scores_codex":[0.8953595,0.08391123,0.005389565,0.002142439,0.006424263,0.006772954],"domain_scores_gemma":[0.952012,0.02755238,0.001726858,0.001608412,0.01339587,0.003704499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003501215,0.000511088,0.006915044,0.003309588,0.000160156,0.001854637,0.7706988,0.003990394,0.006441929,0.04487089,0.01965853,0.1412388],"study_design_scores_gemma":[0.0001145634,0.0004617053,0.004066802,0.004218879,0.00007113587,0.0006555128,0.8757769,0.006431704,0.002053784,0.03930067,0.06663967,0.0002086887],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5340421,0.003077732,0.2082585,0.1459914,0.001996738,0.0357658,0.0004693328,0.0003057533,0.07009269],"genre_scores_gemma":[0.8466542,0.002317943,0.127229,0.008426097,0.0001238627,0.0107393,0.0002049336,0.00006999617,0.004234712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1488971,"threshold_uncertainty_score":0.7874525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1406907151008077,"score_gpt":0.4747872876642197,"score_spread":0.334096572563412,"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."}}