{"id":"W6920274593","doi":"10.6068/dp14ba8f1306c55","title":"Trend 2007 - 2011. Statistics Canada. CANSIM: Ethnic Diversity and Immigration - Labor Market and Income | Country: Canada | Table: Labour force survey estimates (LFS), by immigrant status, educational attainment, sex and age group | Variable: 25 to 54 years, Not in labour force, High school graduate, some post-secondary, Males, Immigrants, landed more than 5 to 10 years earlier | Units: , 2007-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-094.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Quasicrystal Structures and Properties","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Unemployment; Census; Official statistics; Socioeconomic status; Descriptive statistics; Population; Ethnic group; Diversity (politics); Government (linguistics)","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":[0.00272109,0.002466735,0.002970153,0.007943925,0.003458069,0.004668596,0.005548346,0.001484021,0.08460362],"category_scores_gemma":[0.01815108,0.002029019,0.00248903,0.0371754,0.0006174204,0.002330411,0.002472888,0.003455843,0.0447579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05731418,"about_ca_system_score_gemma":0.1539652,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996165,"about_ca_topic_score_gemma":0.9950033,"domain_scores_codex":[0.9951146,0.0003567062,0.0005495892,0.0005432138,0.002239724,0.001196243],"domain_scores_gemma":[0.9607049,0.001259868,0.001192012,0.0009808649,0.03392371,0.00193871],"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":[0.00003421469,0.000009880076,0.001566368,0.0002768412,0.00002740427,0.000007580035,0.00002917478,0.000102812,0.00001093028,0.0003205132,0.9955047,0.002109595],"study_design_scores_gemma":[0.0002465479,0.00002340091,0.05053563,0.001324016,0.0001166877,0.00003736996,0.0007809598,0.000619162,0.0002329798,0.0007016373,0.945255,0.0001265513],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009434047,0.00006768462,0.00003213167,0.0001733154,0.00004529938,0.0000259417,0.9984375,0.00006237254,0.001061375],"genre_scores_gemma":[0.001255712,0.0003859443,0.0005330615,0.0002745104,0.00002865851,0.0002111814,0.9903633,0.0001399673,0.006807663],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08460362,"threshold_uncertainty_score":0.4158455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01733854489628795,"score_gpt":0.2369314805244407,"score_spread":0.2195929356281527,"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."}}