{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001899587,0.001348321,0.001823847,0.0002734877,0.0004101412,0.0005744869,0.001694497,0.0007118393,0.001726802],"category_scores_gemma":[0.0002531329,0.001309966,3.84069e-7,0.0008997877,0.0004552844,0.0005845942,0.002578114,0.0009961292,0.00004010611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000441147,"about_ca_system_score_gemma":0.005027607,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999641,"about_ca_topic_score_gemma":0.9999791,"domain_scores_codex":[0.9921706,0.001242081,0.001121349,0.00212789,0.001712245,0.001625798],"domain_scores_gemma":[0.9934382,0.001462358,0.0009042899,0.002520253,0.000149798,0.001525066],"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":[0.0009361551,0.00009881592,0.007003226,0.0006789973,0.0006589323,0.001120784,0.00002134915,0.000007376283,0.00001237016,0.00003359937,0.9893247,0.0001036766],"study_design_scores_gemma":[0.002612205,0.000170036,0.006384025,0.0001035606,0.0007340562,0.0001226763,0.0004395244,0.001095867,2.923721e-8,3.057952e-7,0.9867181,0.001619644],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002477806,0.008921762,0.000009273568,0.000003714159,0.0003741735,0.001458847,0.9887931,0.0001306225,0.00006066346],"genre_scores_gemma":[0.0001036132,0.005627698,0.000362437,0.0002538309,0.00008987212,0.00003026602,0.9806283,0.000515388,0.01238862],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01232795,"threshold_uncertainty_score":0.9999268,"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."}}