{"id":"W6976516652","doi":"10.6068/dp14ba841b4dc94","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: Hungary, Canadian students, Both sexes, University | 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; Ethnic group; Official 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":[0.002488515,0.002448682,0.002914787,0.008519129,0.003745219,0.005252288,0.005411715,0.001694211,0.08701823],"category_scores_gemma":[0.02108741,0.001835183,0.002462467,0.03922619,0.0006721895,0.002749454,0.002548641,0.003313808,0.05121203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0494852,"about_ca_system_score_gemma":0.1431606,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941128,"about_ca_topic_score_gemma":0.9914213,"domain_scores_codex":[0.9950761,0.0003560132,0.0005519405,0.0006249658,0.002255713,0.001135227],"domain_scores_gemma":[0.9635772,0.001364136,0.00106489,0.001127033,0.03118345,0.001683282],"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":[0.00002770704,0.000006796769,0.001155396,0.0002642739,0.0000251353,0.000007311255,0.00002329674,0.0001117609,0.000009761061,0.000391833,0.9962895,0.001687311],"study_design_scores_gemma":[0.0001778764,0.00001323159,0.02321379,0.001075142,0.0000897233,0.00003101955,0.0005395937,0.0005071693,0.0001920257,0.0007688341,0.9732875,0.0001041271],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005268829,0.00005445175,0.00002759188,0.0001505523,0.00003640385,0.00001603428,0.9987323,0.00005886285,0.0008710606],"genre_scores_gemma":[0.000861658,0.0003370868,0.0004656352,0.0002018752,0.00002311062,0.0001444685,0.9938929,0.0001334407,0.003939815],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08701823,"threshold_uncertainty_score":0.3590419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01966412441001332,"score_gpt":0.2366229567144353,"score_spread":0.2169588323044219,"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."}}