{"id":"W6939149746","doi":"10.6068/dp14ba8f7f5cb23","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, educational attainment, sex and age group | Variable: 15 years and over, Population, High school graduate, some post-secondary, Females, 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":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Census; Socioeconomic status; Population; Ethnic group; Official statistics; Diversity (politics); Population statistics; American Community Survey","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":[0.002584468,0.002390451,0.002861416,0.007364473,0.003237306,0.00436771,0.005435105,0.001347108,0.0798794],"category_scores_gemma":[0.01801399,0.001992113,0.002333509,0.03540555,0.0006185123,0.002366209,0.002257315,0.003386383,0.04036106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05439928,"about_ca_system_score_gemma":0.1481659,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958552,"about_ca_topic_score_gemma":0.9941939,"domain_scores_codex":[0.9954777,0.0003207574,0.0005380828,0.0005305982,0.002091541,0.00104133],"domain_scores_gemma":[0.9646154,0.001107927,0.001088061,0.0008628842,0.03058011,0.001745563],"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":[0.00003646412,0.00001011149,0.001666637,0.0003021401,0.00002738741,0.00000761317,0.00003152142,0.0001021512,0.00001165037,0.0003167675,0.9953049,0.002182659],"study_design_scores_gemma":[0.0002905275,0.00002508719,0.05670614,0.001454929,0.0001274456,0.00004142554,0.0008285985,0.0005973908,0.0002310602,0.0007369401,0.9388397,0.0001206623],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009787356,0.00007300747,0.00003231418,0.000170688,0.00004793421,0.00002928187,0.9984262,0.00005891966,0.001063827],"genre_scores_gemma":[0.001431844,0.0004764329,0.0006040715,0.0002899144,0.00003075708,0.0002448536,0.9895991,0.0001363547,0.007186582],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0798794,"threshold_uncertainty_score":0.3946962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02131361382451713,"score_gpt":0.2396992053706164,"score_spread":0.2183855915460992,"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."}}