{"id":"W6901507469","doi":"10.6068/dp14ba8bf1fe665","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: 15 years and over, Europe, Unemployment, Both sexes, Immigrants, landed more than 10 years earlier | Units: , 2006-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-094.","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); Summary statistics","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":[0.00281174,0.002564521,0.002974098,0.00775013,0.003381295,0.004856016,0.005766312,0.00148866,0.09787495],"category_scores_gemma":[0.020224,0.002095815,0.002495176,0.03776959,0.0005984632,0.002455383,0.002532328,0.003380826,0.05248176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05316515,"about_ca_system_score_gemma":0.1465138,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948427,"about_ca_topic_score_gemma":0.9926785,"domain_scores_codex":[0.994992,0.0003918196,0.0005936304,0.0005691049,0.002289644,0.001163729],"domain_scores_gemma":[0.9603906,0.001342873,0.001172622,0.001052206,0.03410766,0.001934],"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":[0.00003247094,0.000008869972,0.001200816,0.000258951,0.00002515495,0.00000699453,0.0000251913,0.00009437943,0.000009822526,0.0003178039,0.9961111,0.001908397],"study_design_scores_gemma":[0.0002633982,0.00002112478,0.03845177,0.001353165,0.0001098528,0.00003640385,0.0006578594,0.0005436216,0.0002239144,0.0008120303,0.9574068,0.0001200161],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006939227,0.00005669019,0.00002893928,0.0001468075,0.00004077358,0.00002481593,0.9985468,0.00006175385,0.001024052],"genre_scores_gemma":[0.0009780831,0.0003351906,0.0005222782,0.0002519715,0.00002779868,0.0002163095,0.9911214,0.0001555551,0.006391429],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09787495,"threshold_uncertainty_score":0.385742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01569849615952826,"score_gpt":0.234660398766243,"score_spread":0.2189619026067147,"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."}}