{"id":"W6920100574","doi":"10.6068/dp14ba85a3de228","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, Europe, Employment, Both sexes, Total population | 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; Population; Socioeconomic status; Descriptive statistics; Ethnic group; Summary statistics; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002573407,0.002475734,0.002931858,0.007729974,0.003437799,0.004817211,0.005558722,0.001400768,0.09610076],"category_scores_gemma":[0.01863112,0.001924384,0.002453655,0.03609569,0.0005770772,0.002351287,0.002532414,0.003250794,0.04919103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04993423,"about_ca_system_score_gemma":0.1362887,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.994424,"about_ca_topic_score_gemma":0.9927049,"domain_scores_codex":[0.9955518,0.0003387431,0.000524427,0.0005102459,0.001998574,0.001076219],"domain_scores_gemma":[0.9662774,0.00114403,0.001042468,0.0009317254,0.02881669,0.00178773],"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":[0.00003283544,0.000008809373,0.001397073,0.0002683427,0.00002654638,0.000007662576,0.00002786755,0.00009695243,0.0000104204,0.0003187697,0.9958156,0.001989089],"study_design_scores_gemma":[0.0002692756,0.00002129998,0.04363305,0.001400265,0.0001151959,0.00003978817,0.000680836,0.0005592823,0.0002336314,0.0008458403,0.9520797,0.0001217469],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000740683,0.00005331634,0.00002839782,0.0001357846,0.00003663903,0.00002474654,0.9986221,0.00005929483,0.0009656833],"genre_scores_gemma":[0.0009875695,0.0003216707,0.0005060458,0.0002171603,0.00002546456,0.0002110043,0.9921703,0.0001380511,0.005422712],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9038993,"threshold_uncertainty_score":0.3622999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01718391206345782,"score_gpt":0.2380138025000844,"score_spread":0.2208298904366266,"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."}}