{"id":"W6957944517","doi":"10.6068/dp14ba8508f9e4","title":"Trend 2001 - 2008. Statistics Canada. CANSIM: Government - Revenue and Expenditures | Country: Canada | Table: Reconciliation of estimated federal government revenue and expenditures from budgetary documents to the Financial Management System (FMS), for fiscal year ending March 31 | Variable: Provisional charges (x 1,000,000), Revenue minus expenditures | Units: $CAD, 2001-2008. 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; Census; Official statistics; Publication; State (computer science); Descriptive 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":[0.002236726,0.002527806,0.002530747,0.009612557,0.003218861,0.005107258,0.004816018,0.001445257,0.08176011],"category_scores_gemma":[0.01839569,0.001807138,0.001924062,0.04267084,0.0006283291,0.002491654,0.002117065,0.003117693,0.05344432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0591667,"about_ca_system_score_gemma":0.1412852,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9940733,"about_ca_topic_score_gemma":0.9927149,"domain_scores_codex":[0.9952952,0.0002648689,0.0004691554,0.000546165,0.002369161,0.001055445],"domain_scores_gemma":[0.9599873,0.00128612,0.001270151,0.001114821,0.0347132,0.001628308],"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":[0.00002061737,0.000005593727,0.0007688211,0.0002033701,0.00001648047,0.000005613055,0.00001565913,0.00009089968,0.000007777823,0.0003622131,0.9971323,0.001370587],"study_design_scores_gemma":[0.0001189259,0.000009720489,0.01987085,0.0006927622,0.00005349753,0.00002087843,0.000320483,0.0003759751,0.000176951,0.0005261612,0.9777601,0.00007373631],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004641884,0.00004417813,0.00001861902,0.0001213552,0.00002408766,0.00001215783,0.9987535,0.00005459289,0.000925136],"genre_scores_gemma":[0.0007193985,0.0002528716,0.0003293582,0.0001347647,0.00001652095,0.00009527564,0.9941657,0.00009623053,0.004189898],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08176011,"threshold_uncertainty_score":0.4292865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212385648814039,"score_gpt":0.2521385206321307,"score_spread":0.2300146641439903,"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."}}