{"id":"W6901486980","doi":"10.6068/dp14ba8bc44b663","title":"Trend 1999 - 2009. 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 operating expenses, Non-chain stores, Shoe, clothing accessories and jewellery stores | Units: , 1999-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-177.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Retail trade; Census; Economic statistics; Summary statistics; Retail sales; Official statistics; Clothing; Index (typography); Descriptive 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001362871,0.002578628,0.002511192,0.007968159,0.002223016,0.004181916,0.004890049,0.001184684,0.05987047],"category_scores_gemma":[0.01098326,0.00147935,0.001815041,0.0400733,0.0005426622,0.002323008,0.001800356,0.002718209,0.05873773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03022509,"about_ca_system_score_gemma":0.07247791,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9896957,"about_ca_topic_score_gemma":0.9873252,"domain_scores_codex":[0.9966826,0.0001621546,0.0003250831,0.0004897671,0.001568168,0.0007721839],"domain_scores_gemma":[0.9766555,0.0006462933,0.0008765876,0.000655842,0.02019474,0.0009711093],"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":[0.00002924701,0.000007670951,0.00142868,0.0001932406,0.00002110657,0.000008029632,0.0000139644,0.0001195419,0.00001087645,0.0002261437,0.9966568,0.0012847],"study_design_scores_gemma":[0.0002068298,0.00001857588,0.04259349,0.0007689653,0.00006763581,0.00003405847,0.0004822474,0.0007158166,0.0002573725,0.0004932641,0.9542739,0.00008786027],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006598605,0.00003151204,0.0000132793,0.00005476689,0.0000167217,0.000007894419,0.9992498,0.00003993327,0.0005202033],"genre_scores_gemma":[0.0005351483,0.0001299134,0.0001427512,0.00005748824,0.0000101142,0.00004123427,0.9967591,0.00004564609,0.002278737],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9401295,"threshold_uncertainty_score":0.2192994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03569470082744353,"score_gpt":0.2477918630197354,"score_spread":0.2120971621922919,"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."}}