{"id":"W6939201159","doi":"10.6068/dp14ba7c042d834","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, age group | Variable: 15 years and over, Employment rate, Born in Canada | 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; Socioeconomic status; Population; Official statistics; Ethnic group; Diversity (politics); Current Population Survey; Population statistics","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"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001665059,0.001381656,0.001716455,0.0002384493,0.0004174304,0.0004023316,0.001612507,0.0005285427,0.0007404975],"category_scores_gemma":[0.0001724266,0.001456765,2.716474e-7,0.000693019,0.0003630155,0.0006700857,0.002254617,0.001079417,0.0000130493],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001466859,"about_ca_system_score_gemma":0.01617148,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999999,"about_ca_topic_score_gemma":0.9999999,"domain_scores_codex":[0.991419,0.00120552,0.001345973,0.002150956,0.002108357,0.001770148],"domain_scores_gemma":[0.9938513,0.001177595,0.001095715,0.002371714,0.0001262406,0.001377431],"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":[0.0004040006,0.00008891458,0.007440577,0.0005663707,0.0004290762,0.001799487,0.00001435357,0.00002954389,0.00001180175,0.0000214243,0.9891418,0.00005269431],"study_design_scores_gemma":[0.002527775,0.00009700726,0.01352215,0.000120901,0.0004845943,0.00008612328,0.0003079222,0.002474136,3.200233e-8,2.673273e-7,0.9788563,0.001522804],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002911413,0.01584362,0.000002527014,0.000002581179,0.0005340432,0.001266828,0.9819568,0.00005789538,0.00004452977],"genre_scores_gemma":[0.0002474752,0.009139897,0.00007097959,0.0002704875,0.00005828152,0.00002358038,0.9877678,0.0004117221,0.002009814],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01470462,"threshold_uncertainty_score":0.9998934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02173151866884918,"score_gpt":0.2441675120108973,"score_spread":0.2224359933420481,"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."}}