{"id":"W6976605962","doi":"10.6068/dp14ba81d3d8617","title":"Trend 1989 - 2012. Statistics Canada. CANSIM: Retail and Wholesale - Retail Sales by Type of Product | Country: Canada | Table: Volume of sales of alcoholic beverages in litres of absolute alcohol and per capita 15 years and over, fiscal years ended March 31 | Variable: Total alcoholic beverages, Total sales | Units: Litres x 1,000, 1989-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-176.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Product (mathematics); Retail sales; Commodity; Economic statistics; Per capita; Distribution (mathematics); Census; Summary statistics; Official statistics","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":[0.001590779,0.002464339,0.002502211,0.008239994,0.00262925,0.004056578,0.005033309,0.001278483,0.07903338],"category_scores_gemma":[0.01389151,0.001604469,0.001908781,0.04060195,0.0005645445,0.002382329,0.001890894,0.002683192,0.05783031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03948256,"about_ca_system_score_gemma":0.09398285,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9932089,"about_ca_topic_score_gemma":0.9906454,"domain_scores_codex":[0.9965984,0.0001916923,0.0003582179,0.0004594418,0.00161229,0.0007799851],"domain_scores_gemma":[0.9737268,0.0007615707,0.0008883617,0.0007092708,0.02280235,0.00111167],"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":[0.00002501534,0.000006173158,0.001142453,0.000226856,0.00001853047,0.000006821649,0.00001744767,0.00009993889,0.000008604233,0.0002879754,0.9966652,0.001494979],"study_design_scores_gemma":[0.0001615802,0.00001450557,0.03270684,0.000796189,0.00006417865,0.0000296415,0.0004288479,0.0004981236,0.0001808141,0.0005322177,0.9645068,0.00008022729],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005501052,0.00004072136,0.00001700873,0.0000801337,0.00001858025,0.00001093728,0.9990651,0.00004548648,0.0006669741],"genre_scores_gemma":[0.0007313415,0.0002442853,0.000273345,0.0001030198,0.00001536231,0.00008493262,0.9949841,0.00007959204,0.00348391],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07903338,"threshold_uncertainty_score":0.2864673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02647348842490338,"score_gpt":0.251420745505145,"score_spread":0.2249472570802416,"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."}}