{"id":"W2766513400","doi":"10.1186/s40176-017-0113-3","title":"Correction to: immigration and the rate of population mixing: explorations with a stylized model","year":2017,"lang":"en","type":"article","venue":"IZA Journal of Development and Migration","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Stylized fact; Mixing (physics); Immigration; Economics; Population; Econometrics; Macroeconomics; Political science; Sociology; Demography; Physics; Law","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":[0.00427749,0.001473626,0.001736392,0.003291032,0.001932734,0.003306894,0.003238782,0.004523139,0.1556074],"category_scores_gemma":[0.1189231,0.0007902334,0.001178191,0.005139763,0.001499928,0.004238803,0.001874284,0.006483209,0.06293399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003243343,"about_ca_system_score_gemma":0.003880976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.023077,"about_ca_topic_score_gemma":0.02702937,"domain_scores_codex":[0.996963,0.0007908478,0.0005444071,0.0005798563,0.000831371,0.0002905875],"domain_scores_gemma":[0.9545641,0.01688223,0.002072566,0.005988661,0.01900493,0.001487676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005600106,0.000005541916,0.0002582388,0.0001128856,0.00001579555,0.00008661488,0.00005354953,0.0003102017,0.00003269711,0.007557091,0.9842977,0.007213716],"study_design_scores_gemma":[0.0001823061,0.00003065102,0.003384744,0.0004947092,0.00006622799,0.0004516798,0.0002747009,0.0048914,0.0005434505,0.02810084,0.9614674,0.000111876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"empirical","genre_scores_codex":[0.001082768,0.001653258,0.009859585,0.08989472,0.8685949,0.00008364242,0.01448809,0.001370661,0.0129724],"genre_scores_gemma":[0.1407183,0.007298556,0.03071413,0.04678175,0.2895355,0.0006569584,0.0151118,0.006341519,0.4628414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1556074,"threshold_uncertainty_score":0.5205588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04017692424783575,"score_gpt":0.2968400597658215,"score_spread":0.2566631355179858,"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."}}