{"id":"W6920202558","doi":"10.6068/dp14ba8149bc889","title":"Trend 1980 - 2005. Statistics Canada. CANSIM: Government - Government Business Enterprises | Country: Canada | Table: Assets, liabilities and net worth of provincial and territorial government business enterprises, by industry, as at the end of the fiscal year closest to December 31 | Variable: Bonds and debentures, Communication | Units: $CAD x 1,000, 1980-2005. 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; Official statistics; Census; Goods and services; Business statistics; State (computer science); Politics; National accounts","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":[0.001622019,0.002256563,0.002426062,0.009234727,0.003123648,0.004848616,0.004894555,0.001415604,0.07220507],"category_scores_gemma":[0.01478902,0.001681519,0.001721988,0.0419865,0.000614546,0.002542987,0.001986922,0.0030729,0.04635177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05754546,"about_ca_system_score_gemma":0.1374629,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953441,"about_ca_topic_score_gemma":0.9940639,"domain_scores_codex":[0.9961069,0.0001853562,0.0003828407,0.00047618,0.001927862,0.0009208577],"domain_scores_gemma":[0.9694903,0.0009337266,0.00109297,0.0007907094,0.02632147,0.001370845],"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":[0.00001992566,0.000007041662,0.001203504,0.000203866,0.00001821221,0.00000739622,0.00002184037,0.0001214708,0.000008691984,0.0004545817,0.996439,0.001494493],"study_design_scores_gemma":[0.0001152519,0.00001119998,0.02708003,0.0006888271,0.00005673996,0.00002492168,0.000489349,0.0004648842,0.0001869228,0.0005951267,0.9702128,0.00007396081],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007673427,0.00005462665,0.00002021683,0.00011408,0.00002291123,0.00001202089,0.9986947,0.00004863174,0.0009560377],"genre_scores_gemma":[0.001086516,0.0003073998,0.0002981124,0.0001267891,0.00001762017,0.00009269043,0.9930834,0.0000804527,0.004907047],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07220507,"threshold_uncertainty_score":0.4175235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01053067573289725,"score_gpt":0.2227596633903842,"score_spread":0.212228987657487,"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."}}