{"id":"W6976531827","doi":"10.6068/dp14ba8f8de2618","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, educational attainment, sex and age group | Variable: 15 years and over, Unemployment rate, No degree, certificate or diploma, Both sexes, Immigrants, landed more than 5 to 10 years earlier | 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":"Climate Change and Geoengineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Socioeconomic status; Census; Population; Official statistics; Population statistics; Unemployment; Nationality; Ethnic group","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":[],"category_scores_codex":[0.0005427862,0.0005828066,0.0006212078,0.00007247972,0.0002474067,0.0002156597,0.0005790525,0.0002295262,0.001495165],"category_scores_gemma":[0.00004236239,0.0005500045,3.152127e-7,0.000235075,0.0002051182,0.0003011716,0.001350081,0.0003028084,0.00001387038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002134814,"about_ca_system_score_gemma":0.0004950456,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9998403,"about_ca_topic_score_gemma":0.9996454,"domain_scores_codex":[0.9966974,0.0001880738,0.0004841109,0.001098018,0.0007965107,0.000735936],"domain_scores_gemma":[0.9977618,0.0003683319,0.0002841812,0.0008824545,0.00001749234,0.0006857406],"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":[0.0001847708,0.00005629001,0.007719117,0.0002131003,0.0001320144,0.0001508086,0.00004755865,0.00002051847,0.00003211615,0.000002814174,0.9913024,0.0001385053],"study_design_scores_gemma":[0.0008352025,0.00008267687,0.04386171,0.00004851018,0.0001648555,0.00003281019,0.0002310578,0.001403556,5.885158e-8,2.017301e-7,0.9526883,0.0006510816],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002208041,0.003271162,0.000003410527,0.000007431593,0.0001818131,0.0006458524,0.9936273,0.00002604925,0.00002894929],"genre_scores_gemma":[0.0003367612,0.006759323,0.00009246724,0.000182384,0.00004563244,0.00001866559,0.9854187,0.0001065525,0.00703954],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03861411,"threshold_uncertainty_score":0.9996951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03938470420968535,"score_gpt":0.2570315167093774,"score_spread":0.217646812499692,"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."}}