{"id":"W7095148718","doi":"","title":"Immigrant Economic and Social Outcomes in Canada: Research and Data Development at Statistics Canada. Catalogue No","year":2008,"lang":"en","type":"article","venue":"","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration; Data collection; Statistical analysis; Social research; Data source","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":[0.002559729,0.001012272,0.001441892,0.01474354,0.002385459,0.003180123,0.003037512,0.0007561932,0.04814903],"category_scores_gemma":[0.01560556,0.001120252,0.001124336,0.05126635,0.0007465314,0.001132862,0.001713752,0.001030827,0.01287879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03633383,"about_ca_system_score_gemma":0.1480133,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9971118,"about_ca_topic_score_gemma":0.9963176,"domain_scores_codex":[0.9965509,0.0002186504,0.0004654866,0.0002112442,0.001805647,0.0007481283],"domain_scores_gemma":[0.9722489,0.002176804,0.001319345,0.0008919613,0.02077436,0.002588724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001362069,0.00006276202,0.06267628,0.0009513261,0.00006190653,0.00005058194,0.0003374055,0.0005212022,0.00009034258,0.001267672,0.886466,0.04737836],"study_design_scores_gemma":[0.0001302624,0.00006273528,0.6643593,0.001177786,0.0001043351,0.00008609244,0.001479139,0.0007757378,0.0004890375,0.0005183623,0.3307088,0.0001083427],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.005350855,0.001450301,0.0001673165,0.0006332959,0.00008541391,0.0001914238,0.9805698,0.0002331276,0.01131853],"genre_scores_gemma":[0.02935628,0.005501358,0.001408226,0.0002872612,0.00006745948,0.0004923948,0.9242674,0.0002928815,0.03832687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04814903,"threshold_uncertainty_score":0.2636216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09071846020264754,"score_gpt":0.317747298859876,"score_spread":0.2270288386572285,"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."}}