{"id":"W6976516216","doi":"10.6068/dp14ba8361f8495","title":"Trend 1999 - 2004. Statistics Canada. CANSIM: Retail and Wholesale - Retail Sales by Type of Store | Country: Canada | Table: Annual retail store survey, financial estimates by store type and trade group based on the North American Industry Classification System (NAICS) | Variable: Total revenue, Total all stores, Clothing stores | Units: , 1999-2004. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-177.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Impulse Buying and Technology Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Retail trade; Census; Economic statistics; Summary statistics; Retail sales; Official statistics; Descriptive statistics; Index (typography); Financial services","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":[0.001567476,0.00278479,0.002681517,0.008725594,0.002552856,0.004788191,0.005507007,0.001282048,0.07570618],"category_scores_gemma":[0.01257933,0.001663683,0.001864311,0.0430453,0.0005915519,0.002680101,0.001982487,0.00282175,0.07223164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0325986,"about_ca_system_score_gemma":0.08064715,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9894764,"about_ca_topic_score_gemma":0.9866247,"domain_scores_codex":[0.9963199,0.0001863637,0.0003526733,0.000534329,0.001729862,0.0008769089],"domain_scores_gemma":[0.9722695,0.0007876452,0.000989339,0.0008168692,0.02398319,0.001153408],"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":[0.0000261964,0.000007035498,0.001202544,0.0001740052,0.00001818853,0.000007130933,0.00001403755,0.0001054534,0.000009253882,0.0002259995,0.9969339,0.00127619],"study_design_scores_gemma":[0.000184387,0.00001640074,0.03394618,0.0007257641,0.00005993836,0.00003007214,0.000444873,0.0006320114,0.0002208912,0.0005144652,0.9631415,0.00008349287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000585649,0.00002712916,0.00001468322,0.00005686008,0.00001661765,0.000008786205,0.9991856,0.00004592771,0.0005859052],"genre_scores_gemma":[0.0004814908,0.0001226281,0.0001597201,0.00005965232,0.00001026222,0.00005054681,0.9965279,0.0000591526,0.002528798],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07570618,"threshold_uncertainty_score":0.2532624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04160522735392621,"score_gpt":0.2293709053840179,"score_spread":0.1877656780300916,"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."}}