{"id":"W6939194456","doi":"10.6068/dp14ba88f4d7791","title":"Trend 1988 - 2008. Statistics Canada. CANSIM: Government - Revenue and Expenditures | Country: Canada | Table: Local general government revenue and expenditures, current and capital accounts, year ending December 31 | Variable: Current account, Local government enterprises, grants in lieu of taxes, revenue | Units: $CAD x 1,000, 1988-2008. 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 revenue; Government (linguistics); Official statistics; Capital expenditure; Descriptive statistics; Census","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":[0.00203544,0.002383454,0.002509344,0.00942615,0.003242841,0.004568385,0.004879363,0.001284506,0.08161271],"category_scores_gemma":[0.01603252,0.001719683,0.001640802,0.04377611,0.0005960438,0.002598055,0.00204297,0.002953235,0.05622501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05500928,"about_ca_system_score_gemma":0.1296621,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9943652,"about_ca_topic_score_gemma":0.9931738,"domain_scores_codex":[0.9959252,0.0002311491,0.0003746439,0.0005066028,0.001971339,0.0009910555],"domain_scores_gemma":[0.9663633,0.0009708945,0.001118549,0.0009739675,0.02903416,0.001539138],"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":[0.0000204913,0.000005538567,0.0009314028,0.0001752192,0.00001460191,0.000005900459,0.00002001147,0.0000843841,0.000007472535,0.0003658542,0.9969826,0.001386547],"study_design_scores_gemma":[0.0001041961,0.000009635209,0.0224224,0.0006138154,0.00004709534,0.00002129633,0.000411417,0.0003595873,0.0001517646,0.0005143068,0.9752773,0.0000670309],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005910317,0.00004128066,0.00001902288,0.0001043542,0.00002072919,0.00001170316,0.9988021,0.00005269926,0.0008890118],"genre_scores_gemma":[0.000822057,0.0002333395,0.000328779,0.0001107452,0.00001506569,0.0001024448,0.99386,0.00009400733,0.004433546],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08161271,"threshold_uncertainty_score":0.3991221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01647704419587946,"score_gpt":0.2471077085578609,"score_spread":0.2306306643619814,"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."}}