{"id":"W6920503009","doi":"10.6068/dp14ba88238fa74","title":"Trend 1999 - 2011. Statistics Canada. CANSIM: Ethnic Diversity and Immigration - Education, Training and Skills | Country: Canada | Table: Postsecondary graduates, by immigration status, country of citizenship and sex | Variable: Korea, North, International Students, Males, Total, institution type | Units: #, 1999-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-089.","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; Citizenship; Population; Statistics education; Socioeconomic status; Official statistics; Ethnic group","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":[0.002513213,0.002416505,0.002885274,0.008209177,0.003286478,0.005106183,0.005352303,0.001583607,0.08692822],"category_scores_gemma":[0.02089152,0.001853872,0.002357981,0.03992967,0.0006556379,0.002712975,0.002429733,0.003147813,0.05486736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04441929,"about_ca_system_score_gemma":0.1295044,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9914749,"about_ca_topic_score_gemma":0.9875448,"domain_scores_codex":[0.9951313,0.0003517735,0.0005547527,0.0006216139,0.002245508,0.001095107],"domain_scores_gemma":[0.9612815,0.001495859,0.001192271,0.001235863,0.03303849,0.001755946],"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":[0.00002687529,0.000006776035,0.001077852,0.0002449441,0.00002217376,0.000006325929,0.00001957331,0.0001054921,0.000008964973,0.0003320487,0.9966376,0.001511363],"study_design_scores_gemma":[0.0001876857,0.0000136225,0.02396595,0.001072974,0.00008085707,0.00002756638,0.0004792778,0.000470866,0.0001979566,0.0007131091,0.9726939,0.00009634605],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004570853,0.00004161063,0.00002288023,0.0001178639,0.00002979077,0.00001436505,0.998915,0.00005575207,0.0007571192],"genre_scores_gemma":[0.0006981923,0.000267078,0.0003845018,0.0001628875,0.00002069638,0.0001375269,0.9947301,0.0001240375,0.003474878],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08692822,"threshold_uncertainty_score":0.322286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02356212271309492,"score_gpt":0.2550346946241847,"score_spread":0.2314725719110898,"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."}}