{"id":"W2154386065","doi":"10.1016/j.puhe.2014.01.010","title":"Defining migration and its health impact in China","year":2014,"lang":"en","type":"review","venue":"Public Health","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":60,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Urbanization; Internal migration; China; Government (linguistics); Public health; Census; Economic growth; Politics; Rural area; Population; Scale (ratio); Health care; Political science; Health policy; Public policy; Development economics; Geography; Environmental health; Medicine; Economics; 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":[0.003412954,0.001103718,0.002290693,0.00754658,0.0005532161,0.001810579,0.000912189,0.001109369,0.003585951],"category_scores_gemma":[0.003928589,0.0003875062,0.001900749,0.01373426,0.001032336,0.001451308,0.001680386,0.0007997265,0.0001472625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002942,"about_ca_system_score_gemma":0.01455076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05723969,"about_ca_topic_score_gemma":0.1233703,"domain_scores_codex":[0.9991499,0.0002158732,0.0002496768,0.00008871905,0.0002070245,0.00008876567],"domain_scores_gemma":[0.9982262,0.0009168278,0.0004834728,0.00003444155,0.0002446292,0.00009431386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002943839,0.000114455,0.01689313,0.3002154,0.00410222,0.0003854582,0.001228629,0.0009166356,0.0003994824,0.00406929,0.01014641,0.6612346],"study_design_scores_gemma":[0.0003299972,0.0008740366,0.1922588,0.3215631,0.02931496,0.001246734,0.005775157,0.0006079875,0.0008079942,0.00491051,0.4420725,0.0002383193],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001111714,0.9980775,0.00002267631,0.0003461531,0.00009609425,0.000009003365,0.0000624498,0.000001363552,0.0002729358],"genre_scores_gemma":[0.01037381,0.9889582,0.00007647018,0.0003204133,0.0001015841,0.00001174464,0.00004740092,6.235733e-7,0.0001096482],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.05723969,"threshold_uncertainty_score":0.113813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1840986112960987,"score_gpt":0.5294814529255162,"score_spread":0.3453828416294175,"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."}}