{"id":"W6958090640","doi":"10.6068/dp14ba86d4ed16","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, Unemployment, Males, Landed immigrants | 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; Official statistics; Census; Descriptive statistics; Socioeconomic status; Population; Ethnic group; Summary statistics; 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":[0.001573501,0.001267344,0.001970024,0.0002692964,0.0003219439,0.000311942,0.001506328,0.0005817473,0.001147738],"category_scores_gemma":[0.0002539422,0.001287807,3.402506e-7,0.001042338,0.0005972867,0.0004863433,0.002170437,0.0008382908,0.0000181314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003741731,"about_ca_system_score_gemma":0.004294808,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.999981,"about_ca_topic_score_gemma":0.999952,"domain_scores_codex":[0.9926512,0.001113254,0.001250042,0.001845445,0.001736205,0.001403849],"domain_scores_gemma":[0.9933294,0.00155551,0.001325769,0.002379784,0.0001791651,0.001230392],"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":[0.0005738576,0.0001107359,0.01046882,0.00102257,0.000604259,0.0004120268,0.00002549308,0.00001196835,0.00002474149,0.00004714479,0.9866216,0.00007681485],"study_design_scores_gemma":[0.002074157,0.0001906263,0.007753323,0.0001116662,0.0005824405,0.00006491414,0.0003725122,0.001678691,4.184941e-8,3.737928e-7,0.985789,0.001382229],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001917993,0.009036887,0.00001111445,0.00000285031,0.0002725795,0.001215685,0.9890851,0.00009924135,0.00008468345],"genre_scores_gemma":[0.0001842305,0.00705329,0.0003662634,0.0002418348,0.00006486139,0.00002043484,0.9871646,0.0004130913,0.004491367],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.004406684,"threshold_uncertainty_score":0.9997653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01918339824794025,"score_gpt":0.2406635088624553,"score_spread":0.2214801106145151,"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."}}