{"id":"W6938918584","doi":"10.6068/dp14ba8830e8165","title":"Trend 1980 - 2005. Statistics Canada. CANSIM: Government - Government Business Enterprises | Country: Canada | Table: Income and expenses of local government business enterprises, by industry, end of fiscal year closest to December 31 | Variable: Sales of goods and services, Gas distribution, Provincial government | 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; Local government; Politics; Fiscal year; 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","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0009339371,0.001664338,0.002446816,0.00004997763,0.0001586429,0.0002289606,0.002544727,0.0008869495,0.001287013],"category_scores_gemma":[0.0002142696,0.001645216,0.00000102679,0.0005473698,0.0009082307,0.0004574324,0.003226658,0.0009104597,0.000008651038],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004573965,"about_ca_system_score_gemma":0.009534183,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9978791,"about_ca_topic_score_gemma":0.9972716,"domain_scores_codex":[0.9857712,0.0005183325,0.002486346,0.002022928,0.007758009,0.001443157],"domain_scores_gemma":[0.9916309,0.0008173544,0.002892494,0.003191212,0.0001651765,0.001302856],"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":[0.001641471,0.0008327398,0.002173654,0.003365468,0.0009082668,0.0002733759,0.0000070439,0.00006237734,0.00008012003,0.0002675097,0.9901809,0.0002071429],"study_design_scores_gemma":[0.002658077,0.0002484661,0.0005651446,0.0005669934,0.001276018,0.0001494196,0.001092494,0.0004514944,0.000007297722,1.465544e-7,0.9915355,0.001448901],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009551533,0.00212932,0.00009908433,0.000009507286,0.0005926879,0.001629197,0.9943146,0.00004351338,0.001086539],"genre_scores_gemma":[0.002173122,0.001065679,0.0001919738,0.000121205,0.0001999681,0.0000656238,0.9945641,0.0004433757,0.001174986],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007592833,"threshold_uncertainty_score":0.9996259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027754680379002,"score_gpt":0.221905405926225,"score_spread":0.2116278591224349,"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."}}