{"id":"W6939333720","doi":"10.6068/dp14ba8cc454d53","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: 15 years and over, Latin America, Unemployment, Both sexes, Immigrants, landed more than 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":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002840837,0.00256173,0.00300411,0.007866682,0.00339542,0.004914667,0.005815602,0.001471002,0.09458844],"category_scores_gemma":[0.01972857,0.00207303,0.002572858,0.03794165,0.0006003267,0.002429926,0.002548616,0.003366301,0.05141414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05275185,"about_ca_system_score_gemma":0.1462678,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948789,"about_ca_topic_score_gemma":0.9929454,"domain_scores_codex":[0.9949862,0.0003872754,0.000586622,0.0005756379,0.002283382,0.001180914],"domain_scores_gemma":[0.9596925,0.001292693,0.00116917,0.001061377,0.03483769,0.001946547],"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":[0.00003336829,0.000009324734,0.001315416,0.0002644476,0.00002654746,0.000007256918,0.00002600647,0.00009717838,0.00001025637,0.0003274232,0.9958753,0.002007511],"study_design_scores_gemma":[0.0002493354,0.00002094661,0.04026202,0.001313514,0.000108818,0.00003647737,0.0006551285,0.0005234189,0.0002211029,0.0007983329,0.9556924,0.0001185826],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007429165,0.00006015209,0.00002994092,0.000153827,0.00004279585,0.00002555886,0.9985098,0.00006165188,0.001041871],"genre_scores_gemma":[0.001025517,0.0003535768,0.0005425747,0.0002602466,0.00002840523,0.0002196658,0.990926,0.0001519794,0.006492075],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09458844,"threshold_uncertainty_score":0.3827432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01395878476755106,"score_gpt":0.2189473194990378,"score_spread":0.2049885347314867,"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."}}