{"id":"W6901472870","doi":"10.6068/dp14ba8a5a1dd88","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, educational attainment, sex and age group | Variable: 15 years and over, Labour force, Total, all education levels, Females, Total population | 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; Census; Socioeconomic status; Official statistics; Population; Descriptive statistics; Ethnic group; Diversity (politics); Government (linguistics)","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":[0.001364237,0.001021203,0.001093757,0.000224268,0.0004774341,0.0005230348,0.0006970703,0.0005489085,0.001257947],"category_scores_gemma":[0.0002271989,0.001115153,3.223932e-7,0.0005085308,0.0003400023,0.0009774953,0.001349889,0.0006705874,0.000007157638],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006412102,"about_ca_system_score_gemma":0.00636542,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999243,"about_ca_topic_score_gemma":0.9997219,"domain_scores_codex":[0.9942231,0.0008367101,0.0009396312,0.001663323,0.001330706,0.00100654],"domain_scores_gemma":[0.995234,0.00108994,0.001072281,0.001474538,0.000158517,0.0009707587],"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":[0.0002240552,0.0001343544,0.01115601,0.0007884089,0.0003721854,0.00004891064,0.00001787442,0.00001160777,0.00001219578,0.0004159428,0.9867148,0.0001036902],"study_design_scores_gemma":[0.001315427,0.00008940895,0.06347228,0.00006942204,0.00046143,0.0001593087,0.0003232808,0.002127819,9.92421e-9,0.000002905735,0.9308349,0.001143735],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008515987,0.01315944,0.000006492356,0.000007657954,0.0004863843,0.001114722,0.9842413,0.00005918401,0.00007319568],"genre_scores_gemma":[0.0007227085,0.003431971,0.0003555228,0.0002131702,0.000147308,0.00002902492,0.9848207,0.0002978693,0.009981772],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05587979,"threshold_uncertainty_score":0.9996551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02487190221562863,"score_gpt":0.2632344334813846,"score_spread":0.238362531265756,"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."}}