{"id":"W6920334417","doi":"10.6068/dp14ba8864d1e16","title":"Trend 2005 - 2009. Statistics Canada. CANSIM: Government - Revenue and Expenditures | Country: Canada | Table: Federal, provincial and territorial general government revenue and expenditures, for fiscal year ending March 31 | Variable: Provincial and territorial general government, Interest income (x 1,000,000) | Units: $CAD, 2005-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-107.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Revenue; Economic statistics; Government (linguistics); Government revenue; Official statistics; Census; Personal income; State (computer science); Summary 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":[0.002136525,0.002324492,0.002542393,0.00849054,0.003151853,0.004880424,0.004752287,0.001336356,0.09134544],"category_scores_gemma":[0.01707601,0.00172871,0.001847671,0.04018604,0.0005888877,0.002557877,0.002029343,0.00290304,0.05768375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05674715,"about_ca_system_score_gemma":0.1358247,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944119,"about_ca_topic_score_gemma":0.9927625,"domain_scores_codex":[0.9957263,0.0002516797,0.0004292433,0.0005023123,0.002120448,0.0009699734],"domain_scores_gemma":[0.9674993,0.001020376,0.001017679,0.0009298759,0.0280201,0.00151254],"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":[0.0000205337,0.000005453929,0.0007687145,0.000181497,0.00001501783,0.000005898386,0.00001632381,0.00009009284,0.000007444776,0.0003762671,0.9970278,0.001484992],"study_design_scores_gemma":[0.0001104289,0.00001009114,0.01993061,0.0007065948,0.00005063586,0.0000224462,0.0003616853,0.0004062322,0.0001614455,0.0005941682,0.9775736,0.00007199065],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005276827,0.0000515965,0.00002427469,0.0001382634,0.00003013647,0.00001376178,0.9984681,0.0000600306,0.001161037],"genre_scores_gemma":[0.0009480409,0.000328362,0.0004466953,0.0001753651,0.00002032863,0.0001127063,0.9920213,0.0001277089,0.005819491],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09134544,"threshold_uncertainty_score":0.4117313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01874535498307512,"score_gpt":0.2476273037847657,"score_spread":0.2288819488016906,"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."}}