{"id":"W6901762159","doi":"10.6068/dp14ba8a89e0654","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, Europe, Unemployment rate, Both sexes, Total population | 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; Population; Official statistics; Socioeconomic status; Population statistics; Ethnic group; Unemployment; Diversity (politics)","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":[0.002568845,0.002423652,0.002905914,0.007405972,0.003249502,0.00485255,0.005528806,0.001389102,0.09292205],"category_scores_gemma":[0.01921163,0.001995274,0.00226052,0.03563729,0.0005887906,0.00244356,0.002430506,0.003277894,0.05034087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04814925,"about_ca_system_score_gemma":0.1279424,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9939614,"about_ca_topic_score_gemma":0.9915174,"domain_scores_codex":[0.9956775,0.0003322741,0.0005308973,0.0005377306,0.001896299,0.00102531],"domain_scores_gemma":[0.9671878,0.001197442,0.001037668,0.0009321465,0.02793243,0.001712636],"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":[0.00003011275,0.000007958815,0.001219292,0.0002502261,0.00002264822,0.000006827977,0.00002733552,0.00008962894,0.000009422887,0.0002980949,0.9962379,0.001800464],"study_design_scores_gemma":[0.0002814564,0.00001977416,0.0400636,0.001393991,0.0001050666,0.00003882496,0.0006962019,0.0005345981,0.0002066466,0.0008278138,0.9557207,0.0001113237],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006689027,0.00004988558,0.00002656672,0.0001311449,0.00003507309,0.00002315127,0.9987204,0.00005582403,0.0008910627],"genre_scores_gemma":[0.0009233594,0.0003325286,0.0004761569,0.0002135046,0.00002499617,0.0002155544,0.9925574,0.0001346887,0.005121785],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09292205,"threshold_uncertainty_score":0.3493488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0187327933205231,"score_gpt":0.2409893096539295,"score_spread":0.2222565163334064,"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."}}