{"id":"W6938877741","doi":"10.6068/dp14ba82e163323","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: Retained earnings opening balance, 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; Earnings; Census; Politics; Goods and services; Index (typography)","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":[0.001724827,0.002349238,0.00254527,0.008758022,0.003413475,0.005182085,0.005098241,0.001523148,0.08132653],"category_scores_gemma":[0.01674989,0.001634312,0.001884499,0.04114431,0.0006433811,0.002642736,0.002265118,0.003074038,0.06319229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04520794,"about_ca_system_score_gemma":0.1145457,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9928001,"about_ca_topic_score_gemma":0.9918024,"domain_scores_codex":[0.9962243,0.0002208104,0.0003982807,0.0005266543,0.001729818,0.0009001238],"domain_scores_gemma":[0.9681488,0.00109113,0.001013994,0.001026817,0.02734863,0.001370546],"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":[0.00001841849,0.000005510397,0.0008356447,0.0001691791,0.00001467654,0.000006401268,0.00001646965,0.00008242497,0.000007274501,0.0002963259,0.99735,0.001197463],"study_design_scores_gemma":[0.0001179323,0.000009575232,0.01992577,0.0007033254,0.00005212668,0.0000243544,0.0004198146,0.0004275792,0.0001643598,0.0006163597,0.9774659,0.0000729092],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004727881,0.00003962914,0.00001743465,0.00009781526,0.0000215959,0.00000962151,0.9990178,0.00004646528,0.0007023536],"genre_scores_gemma":[0.0005506866,0.0001882306,0.0002231279,0.00009870391,0.00001423577,0.00007006135,0.9958287,0.00007142131,0.002954813],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08132653,"threshold_uncertainty_score":0.3280081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01226927951620408,"score_gpt":0.2230270321237351,"score_spread":0.2107577526075311,"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."}}