{"id":"W6939133307","doi":"10.6068/dp14ba8c7995758","title":"Trend 1999 - 2011. Statistics Canada. CANSIM: Government - Government Business Enterprises | Country: Canada | Table: Balance sheet and income statement of federal government business enterprises, by North American Industry Classification System (NAICS), end of fiscal year closest to December 31 | Variable: Short term paper, asset, Transportation and warehousing and information and cultural industries | 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":"Government (linguistics); Economic statistics; Balance sheet; Income statement; Official statistics; Census; Goods and services; Politics; Business statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004955654,0.0009539565,0.001319355,0.0000647813,0.0001806816,0.0003583132,0.0007135472,0.0003959873,0.0001657538],"category_scores_gemma":[0.00007177299,0.0009061353,3.981459e-7,0.0003609099,0.000501104,0.001346692,0.0004739392,0.0006352051,0.000002180449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001669998,"about_ca_system_score_gemma":0.002998879,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938866,"about_ca_topic_score_gemma":0.9863793,"domain_scores_codex":[0.9932808,0.0002549296,0.001757066,0.001061219,0.002982331,0.0006637077],"domain_scores_gemma":[0.9957938,0.0002975563,0.001879699,0.001218935,0.000173991,0.0006360585],"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":[0.0005324687,0.0001163959,0.03569352,0.002010108,0.0003812364,0.00004343721,0.00002477812,0.00004345443,0.00003765027,0.00003125528,0.9605291,0.0005565853],"study_design_scores_gemma":[0.001239764,0.0001443964,0.02308633,0.0002446593,0.0005993394,0.00006054043,0.002273327,0.0007450458,7.227318e-7,1.406116e-8,0.9707369,0.0008689168],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002033955,0.0006947094,0.00003475369,0.000008081858,0.0002579894,0.001257131,0.9954077,0.00004121703,0.0002644362],"genre_scores_gemma":[0.02089052,0.001474747,0.0001904581,0.00008744081,0.00006210704,0.00005280005,0.976959,0.0001657214,0.0001172402],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01885657,"threshold_uncertainty_score":0.9993389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01329377308598463,"score_gpt":0.2249471463787182,"score_spread":0.2116533732927336,"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."}}