{"id":"W6920328566","doi":"10.6068/dp14ba8c3182885","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, Asia, Not in labour force, Both sexes, Immigrants, landed 5 or less 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":[0.002674378,0.002591227,0.003044993,0.007667772,0.003324187,0.004802972,0.005790441,0.001467927,0.08787585],"category_scores_gemma":[0.01886895,0.001986788,0.002578401,0.03720899,0.0006034456,0.002319554,0.002488341,0.003382288,0.04772082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05377461,"about_ca_system_score_gemma":0.1420649,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953731,"about_ca_topic_score_gemma":0.9938667,"domain_scores_codex":[0.9953085,0.0003520795,0.0005380003,0.0005496074,0.002140168,0.001111639],"domain_scores_gemma":[0.963446,0.001193723,0.001106923,0.0009809259,0.03142266,0.001849774],"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":[0.00003383476,0.000008927949,0.001400559,0.0002682429,0.000028119,0.000007215284,0.00002659414,0.0001009544,0.00001027528,0.0003217944,0.9958942,0.00189938],"study_design_scores_gemma":[0.0002656392,0.00002143964,0.04387472,0.001340952,0.0001166705,0.00003753456,0.0006797626,0.0005672603,0.0002223415,0.0007989751,0.9519517,0.0001230508],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007543699,0.00005972738,0.00002781481,0.0001469561,0.0000393992,0.0000230917,0.9986349,0.00005660703,0.0009360237],"genre_scores_gemma":[0.001067138,0.0003449793,0.0005022323,0.0002489781,0.00002745254,0.0002075176,0.9915614,0.000135512,0.005904772],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08787585,"threshold_uncertainty_score":0.390164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01762065977380876,"score_gpt":0.2371810598059685,"score_spread":0.2195604000321598,"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."}}