{"id":"W6901516956","doi":"10.6068/dp14ba88b078725","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, Labour force, Males, 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; Socioeconomic status; Official statistics; Population statistics; Ethnic group; Diversity (politics); American Community Survey","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":[0.002625505,0.002389815,0.00292116,0.007327991,0.003320695,0.004883229,0.005561715,0.001386333,0.09177828],"category_scores_gemma":[0.01967088,0.00196959,0.002300577,0.03521554,0.0005931123,0.00243814,0.002412146,0.003327766,0.04822857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04905324,"about_ca_system_score_gemma":0.1346854,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941507,"about_ca_topic_score_gemma":0.9918132,"domain_scores_codex":[0.9955412,0.0003405576,0.0005437727,0.0005494118,0.001981036,0.001044006],"domain_scores_gemma":[0.965832,0.00121823,0.001060064,0.0009532018,0.0291772,0.001759275],"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":[0.00003263032,0.000008388787,0.001328385,0.0002661672,0.0000243079,0.000007053867,0.00002861769,0.00009157685,0.000009922013,0.0003125833,0.9959515,0.001938803],"study_design_scores_gemma":[0.0002881567,0.000021186,0.04264349,0.001512695,0.0001135476,0.00004023212,0.0007366158,0.00055437,0.0002124625,0.0008542477,0.9529073,0.000115566],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007375296,0.00005558581,0.00002955811,0.0001442356,0.00003882159,0.0000259328,0.9986145,0.00005888954,0.000958678],"genre_scores_gemma":[0.001065787,0.0003786803,0.0005443555,0.0002438075,0.00002770536,0.0002375989,0.9917113,0.0001446389,0.005646104],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09177828,"threshold_uncertainty_score":0.3559078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01763993374751132,"score_gpt":0.2377881432094207,"score_spread":0.2201482094619093,"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."}}