{"id":"W6920342592","doi":"10.6068/dp14ba8e5951916","title":"Trend 2006 - 2013. Statistics Canada. CANSIM: Ethnic Diversity and Immigration - Immigrants and Nonpermanent Residents | Country: Canada | Table: Labour force survey estimates (LFS), by immigrant status, country of birth, sex and age group | Variable: 15 years and over, North America, Unemployment rate, Both sexes, Immigrants, landed more than 10 years earlier | Units: , 2006-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-092.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Census; Socioeconomic status; Population; Official statistics; Ethnic group; Population statistics; Diversity (politics); Unemployment","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":[0.002602279,0.002380389,0.002894662,0.007415331,0.003292646,0.004628743,0.005374487,0.001348003,0.0853079],"category_scores_gemma":[0.01814788,0.001985783,0.00233863,0.03478207,0.0005851999,0.002344561,0.002309363,0.003341592,0.04401488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05446185,"about_ca_system_score_gemma":0.1483165,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9955522,"about_ca_topic_score_gemma":0.9937827,"domain_scores_codex":[0.9955152,0.000326664,0.0005260145,0.000527825,0.002048116,0.001056251],"domain_scores_gemma":[0.9645484,0.001101385,0.001030268,0.0008520859,0.03065447,0.001813322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003825446,0.000009952773,0.001578253,0.0002922179,0.00002783029,0.000007785968,0.00003140508,0.0001014514,0.00001171815,0.0003265168,0.9952222,0.002352424],"study_design_scores_gemma":[0.0002901591,0.0000250188,0.05327136,0.001442994,0.0001292797,0.00004257343,0.0007909512,0.0005679153,0.0002272891,0.0007850524,0.9423071,0.0001204568],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009937704,0.00007528929,0.00003467073,0.0001768533,0.00004873993,0.00003174279,0.9982473,0.00006831752,0.001217751],"genre_scores_gemma":[0.001379911,0.0004887138,0.0006550471,0.0003028995,0.00003223154,0.0002575862,0.9891818,0.0001594032,0.007542466],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0853079,"threshold_uncertainty_score":0.3951502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01634913072330407,"score_gpt":0.2377514026918639,"score_spread":0.2214022719685598,"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."}}