{"id":"W7095963200","doi":"","title":"Acquisition and Employment Consequences among Southeast Asian Refugees in Canada","year":2015,"lang":"en","type":"article","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Refugee; Population; Immigration; Ethnic group; Cultural background; Southeast asia","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003566031,0.0003108084,0.0004334858,0.001213695,0.00560246,0.001699568,0.0008717241,0.0005425308,0.00313798],"category_scores_gemma":[0.0009637778,0.0003211789,0.0004430168,0.003282623,0.001215853,0.0004160693,0.001545111,0.001134649,0.0003165597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01772009,"about_ca_system_score_gemma":0.02801069,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9913985,"about_ca_topic_score_gemma":0.9973335,"domain_scores_codex":[0.9993964,0.0000275972,0.00003006013,0.00004599667,0.0001331768,0.0003667157],"domain_scores_gemma":[0.9988795,0.00003196985,0.0001700689,0.00002337131,0.0003583773,0.0005367434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001472595,0.0001060522,0.9816289,0.00004037797,0.00004031663,0.0006768789,0.006619609,0.00008280304,0.0004017733,0.0002373903,0.001829566,0.008189055],"study_design_scores_gemma":[0.00001108289,0.00003986635,0.976813,0.00006753046,0.00001868112,0.0001415729,0.0207987,0.0001270939,0.00006941485,0.00004877122,0.001845121,0.00001913389],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969253,0.0003340633,0.00001208978,0.0003837043,0.00001032602,0.00001548367,0.0007712414,0.000002537257,0.001545333],"genre_scores_gemma":[0.9968303,0.0006540458,0.00004061705,0.0001647872,0.000003938199,0.00001008589,0.0005317834,0.000003810155,0.001760652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01772009,"threshold_uncertainty_score":0.1285688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01677386294661693,"score_gpt":0.2744290912499375,"score_spread":0.2576552283033206,"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."}}