{"id":"W6938866383","doi":"10.6068/dp14ba800e3d640","title":"Trend 1999 - 2011. Statistics Canada. CANSIM: Government - Government Business Enterprises | Country: Canada | Table: Balance sheet and income statement of provincial and territorial government business enterprises, by North American Industry Classification System (NAICS), end of fiscal year closest to December 31 | Variable: Gains or losses, Utilities | Units: $CAD x 1,000, 1999-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-105.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Government (linguistics); Balance sheet; Official statistics; Income statement; Census; Politics; Goods and services; Index (typography); Publication","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":[0.001777973,0.002380883,0.002535395,0.008950428,0.003503865,0.005344985,0.00505786,0.001549853,0.08890832],"category_scores_gemma":[0.01709907,0.001696198,0.001933909,0.04257329,0.0006455468,0.002767561,0.002260369,0.003181261,0.06401924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0479733,"about_ca_system_score_gemma":0.1245248,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9932351,"about_ca_topic_score_gemma":0.9920003,"domain_scores_codex":[0.996038,0.0002252572,0.0004174968,0.0005147982,0.001873673,0.000930834],"domain_scores_gemma":[0.9670064,0.001106406,0.00102146,0.001021109,0.02844492,0.001399582],"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":[0.00001842831,0.00000548087,0.0007870967,0.0001808237,0.00001463344,0.000006297179,0.00001688768,0.00008832981,0.000007428181,0.000341094,0.9972817,0.001251766],"study_design_scores_gemma":[0.0001099683,0.000009272149,0.01855818,0.0006948216,0.00005046483,0.00002256712,0.0004231175,0.0003945943,0.0001572647,0.0006020074,0.9789072,0.00007056043],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004872255,0.00004195886,0.00001908794,0.000106722,0.00002379988,0.00001079791,0.9988586,0.00004875894,0.0008415796],"genre_scores_gemma":[0.0006237357,0.0002259745,0.0002597126,0.0001094913,0.00001566,0.000081659,0.9949097,0.00008398385,0.003690115],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08890832,"threshold_uncertainty_score":0.3480723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01721712009537014,"score_gpt":0.2374657655217725,"score_spread":0.2202486454264024,"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."}}