{"id":"W6901462373","doi":"10.6068/dp14ba7d40ff077","title":"Trend 1993 - 2012. Statistics Canada. CANSIM: Government - Government Business Enterprises | Country: Canada | Table: Reconciliation of net income of liquor authorities with total revenue specifically derived from the control and sale of alcoholic beverages, fiscal years ended March 31 | Variable: Add: fines and confiscations | Units: $CAD x 1,000, 1993-2012. 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); Revenue; Official statistics; Goods and services; Census; Government revenue; Descriptive statistics; Control (management); Net income","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":[0.001894528,0.002509059,0.002661891,0.009215637,0.003310342,0.005290949,0.005191043,0.001548055,0.0793792],"category_scores_gemma":[0.01678052,0.001834986,0.002067655,0.04351673,0.0006788041,0.002550629,0.002271984,0.003267111,0.05359545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05590699,"about_ca_system_score_gemma":0.1329709,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9950802,"about_ca_topic_score_gemma":0.993869,"domain_scores_codex":[0.9957013,0.0002357073,0.0004435527,0.0005440308,0.002049432,0.001025979],"domain_scores_gemma":[0.9668283,0.001083238,0.001167136,0.0009610895,0.02847031,0.001489854],"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":[0.00002323521,0.000006578526,0.001077489,0.0002203274,0.00001976329,0.000006765572,0.00001929454,0.0001085509,0.000008569336,0.0003637558,0.9967894,0.0013562],"study_design_scores_gemma":[0.0001489625,0.00001145738,0.02655538,0.000786373,0.00006527229,0.00002427278,0.0004628718,0.0004786293,0.0001973338,0.0005955102,0.9705903,0.00008361091],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005430391,0.00004481981,0.00001798454,0.0001055324,0.00002048713,0.00001106033,0.998922,0.00004855114,0.000775301],"genre_scores_gemma":[0.0008239596,0.0002633886,0.0002876137,0.0001213187,0.00001584054,0.00009121766,0.9944654,0.00008963858,0.003841649],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0793792,"threshold_uncertainty_score":0.4056355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01739643613591631,"score_gpt":0.2220780197429924,"score_spread":0.2046815836070761,"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."}}