{"id":"W6920154879","doi":"10.6068/dp14ba8afc6b923","title":"Trend 2006 - 2013. Statistics Canada. CANSIM: Ethnic Diversity and Immigration - Labor Market and Income | Country: Canada | Table: Labour force survey estimates (LFS), by immigrant status, country of birth, sex and age group | Variable: 25 to 54 years, Asia, Employment, Males, Immigrants, landed more than 5 to 10 years earlier | Units: , 2006-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-094.","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; Unemployment; Official statistics; Census; Descriptive statistics; Socioeconomic status; Population; Ethnic group; 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":[0.002864917,0.002591576,0.00300465,0.007927157,0.00350515,0.004943293,0.005813403,0.001463214,0.09381233],"category_scores_gemma":[0.01989158,0.002048492,0.002599962,0.03802691,0.0006137716,0.002393241,0.002529558,0.003342473,0.05060714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05520885,"about_ca_system_score_gemma":0.150662,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9954235,"about_ca_topic_score_gemma":0.9937464,"domain_scores_codex":[0.9950153,0.0003770704,0.000573896,0.0005721389,0.002267616,0.001194066],"domain_scores_gemma":[0.9601233,0.001300202,0.001150451,0.001070809,0.03439287,0.001962297],"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":[0.00003454379,0.000009088228,0.001336513,0.0002669629,0.00002689986,0.000007447166,0.00002718092,0.00009881086,0.00001065206,0.0003237576,0.9958045,0.002053695],"study_design_scores_gemma":[0.0002508421,0.00002111333,0.04093134,0.001338941,0.0001109948,0.00003653229,0.0006652445,0.0005264357,0.0002241486,0.0007917683,0.9549813,0.0001213333],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000760589,0.00006174717,0.00003038495,0.0001558436,0.00004400285,0.00002567442,0.9984883,0.00006349622,0.00105446],"genre_scores_gemma":[0.001075668,0.0003631474,0.0005568576,0.0002648124,0.00002925937,0.0002251402,0.9906516,0.0001565333,0.006677036],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09381233,"threshold_uncertainty_score":0.4005701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01703395892591979,"score_gpt":0.2412822909156832,"score_spread":0.2242483319897634,"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."}}