{"id":"W6957787039","doi":"10.6068/dp14ba8abec6311","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: Capital account, General services, specific purpose transfers, provincial and territorial | 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 (linguistics); Government revenue; Official statistics; Capital expenditure; Descriptive statistics; Census; State (computer science)","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":[0.002150477,0.002329401,0.002492813,0.009368631,0.003171072,0.004643576,0.004889986,0.001323781,0.08754475],"category_scores_gemma":[0.01653972,0.001816723,0.001684438,0.04387216,0.0005872412,0.002606791,0.002061705,0.0030049,0.05818922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05813599,"about_ca_system_score_gemma":0.1379062,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9943599,"about_ca_topic_score_gemma":0.992732,"domain_scores_codex":[0.9955296,0.0002476379,0.0004139438,0.0005356323,0.002220809,0.001052418],"domain_scores_gemma":[0.9650688,0.00100373,0.001130152,0.0009723062,0.03030108,0.001523905],"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":[0.00002070058,0.000005867501,0.0009175717,0.0001828021,0.00001429092,0.000005870221,0.00001961881,0.00008765096,0.000007631216,0.0003768399,0.9968235,0.001537535],"study_design_scores_gemma":[0.0001021405,0.00001003437,0.02304511,0.0006287438,0.00004709997,0.00002100898,0.0003843716,0.0003491052,0.0001484759,0.0005052885,0.9746935,0.0000650946],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006132644,0.00004811084,0.00002188247,0.0001200393,0.00002477113,0.00001401489,0.9985471,0.00005825283,0.001104383],"genre_scores_gemma":[0.0009374899,0.0002911139,0.000399605,0.0001403591,0.00001815598,0.000125856,0.9920204,0.0001157531,0.005951174],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08754475,"threshold_uncertainty_score":0.4218081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01334947439096308,"score_gpt":0.2276830069968114,"score_spread":0.2143335326058483,"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."}}