{"id":"W6957723003","doi":"10.6068/dp14ba8e0163c49","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, country of birth, sex and age group | Variable: 25 to 54 years, Africa, Unemployment 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: 075-001-092.","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); Unemployment; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002534805,0.002321271,0.002867454,0.00719327,0.003190485,0.004580249,0.005348571,0.001360907,0.08954945],"category_scores_gemma":[0.01809187,0.001978927,0.002337543,0.03440404,0.0005799742,0.002388427,0.002249443,0.003326278,0.04547984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05172557,"about_ca_system_score_gemma":0.1418717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9949843,"about_ca_topic_score_gemma":0.9928507,"domain_scores_codex":[0.9956528,0.0003253582,0.0005303585,0.0005088107,0.001960695,0.001022016],"domain_scores_gemma":[0.9643997,0.001126253,0.001052403,0.0008415835,0.03078996,0.001790187],"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":[0.00003719346,0.000009730385,0.001422132,0.0002984029,0.00002626552,0.000007321913,0.00002786916,0.00009427853,0.00001131503,0.0003142564,0.99555,0.002201209],"study_design_scores_gemma":[0.0003072048,0.00002514503,0.0519749,0.001497143,0.0001278697,0.00004225748,0.0007525995,0.0005601554,0.0002311,0.0007836368,0.9435763,0.0001217388],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009097271,0.0000721094,0.00003288914,0.0001745062,0.00005006509,0.00003136646,0.9982875,0.00006681379,0.001193864],"genre_scores_gemma":[0.001272143,0.0004716217,0.0006208983,0.0003037306,0.00003257462,0.0002570234,0.9895124,0.0001579381,0.00737169],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08954945,"threshold_uncertainty_score":0.375297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02052243108625681,"score_gpt":0.2437679658165912,"score_spread":0.2232455347303344,"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."}}