{"id":"W6938813453","doi":"10.6068/dp14ba88e1d0562","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, sex and detailed age group | Variable: 15 to 24 years, Unemployment, Males, 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)","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":[0.002788713,0.002588441,0.002954197,0.007942209,0.003427465,0.004740597,0.005731037,0.001448973,0.09931498],"category_scores_gemma":[0.01885297,0.002093538,0.002540228,0.03719018,0.0005964451,0.002414301,0.002541787,0.003308757,0.0513911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0529606,"about_ca_system_score_gemma":0.1458038,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9950954,"about_ca_topic_score_gemma":0.9933437,"domain_scores_codex":[0.9951018,0.0003631985,0.0005572879,0.0005504353,0.002242672,0.001184487],"domain_scores_gemma":[0.9624905,0.001234369,0.001140201,0.001036742,0.03212136,0.001976898],"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":[0.00003431094,0.000009271046,0.001443082,0.0002742412,0.00002616841,0.000007395796,0.00002820589,0.00009792033,0.00001128307,0.0003204364,0.99566,0.002087566],"study_design_scores_gemma":[0.0002629008,0.00002315446,0.04653654,0.001406942,0.0001097736,0.0000376357,0.0006929424,0.0005465728,0.0002364929,0.0007817979,0.9492453,0.0001198363],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000771789,0.00005647212,0.00003001804,0.0001416525,0.00003932979,0.00002613271,0.9985074,0.00006139042,0.001060345],"genre_scores_gemma":[0.001063665,0.0003438642,0.000544659,0.0002395493,0.00002661045,0.0002252962,0.9908202,0.0001540181,0.006582115],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09931498,"threshold_uncertainty_score":0.3842579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02692998787813531,"score_gpt":0.2465061691648174,"score_spread":0.2195761812866821,"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."}}