{"id":"W6957801900","doi":"10.6068/dp14ba8d81f827","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, country of birth, sex and age group | Variable: 25 to 54 years, Latin America, Participation rate, 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: 075-001-094.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Marine Toxins and Detection Methods","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Unemployment; Official statistics; Census; Descriptive statistics; Socioeconomic status; Population; Summary statistics; 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":[],"category_scores_codex":[0.00101259,0.0004350685,0.000679604,0.00007636055,0.0001520538,0.0001232486,0.0004923975,0.0002201173,0.002308997],"category_scores_gemma":[0.0001182803,0.0004261724,2.241424e-7,0.0004775987,0.0002133097,0.0002233214,0.001088134,0.0002987653,0.000005500112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001364622,"about_ca_system_score_gemma":0.000552325,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999195,"about_ca_topic_score_gemma":0.9996985,"domain_scores_codex":[0.9968663,0.0005437448,0.0005097976,0.0008395372,0.0006944678,0.0005461476],"domain_scores_gemma":[0.9975551,0.0005257851,0.0003867045,0.0009226264,0.00002321288,0.0005865659],"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":[0.0001841446,0.00003398537,0.009002463,0.0001491724,0.00007641463,0.00005298086,0.00002598002,0.00004261032,0.00002663435,0.000005064102,0.9899128,0.0004877356],"study_design_scores_gemma":[0.0005334743,0.0001198113,0.05364803,0.00001743966,0.0001118453,0.000008366428,0.000156025,0.002196309,7.723974e-8,2.305044e-7,0.9427321,0.0004762823],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008959734,0.000667881,0.00005704251,0.000002730427,0.0001279027,0.0005223273,0.9975991,0.00002741547,0.00009964402],"genre_scores_gemma":[0.0002955549,0.001340329,0.0008719794,0.0002246437,0.00002686543,0.00001208472,0.9911771,0.00007549571,0.005975951],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0471807,"threshold_uncertainty_score":0.999819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597413373996389,"score_gpt":0.2485835479025684,"score_spread":0.2326094141626045,"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."}}