{"id":"W6939213597","doi":"10.6068/dp14ba8bc431062","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, Total all 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":[],"consensus_categories":[],"category_scores_codex":[0.001413922,0.002637184,0.00254401,0.008181624,0.002247115,0.004234753,0.004994975,0.001224026,0.0574321],"category_scores_gemma":[0.01153376,0.001478316,0.001869262,0.04049926,0.0005650726,0.002368922,0.001854354,0.002789561,0.05904533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0301687,"about_ca_system_score_gemma":0.07198108,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9891033,"about_ca_topic_score_gemma":0.9869671,"domain_scores_codex":[0.9966201,0.0001697874,0.0003427092,0.0005163228,0.001584144,0.0007668646],"domain_scores_gemma":[0.9767878,0.0006807034,0.0008949921,0.0006882756,0.01999409,0.0009541491],"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":[0.00002782276,0.000007147909,0.001371536,0.0001935102,0.00002125676,0.000007722359,0.00001325348,0.0001143272,0.00001051496,0.000212635,0.9968125,0.001207687],"study_design_scores_gemma":[0.0002068051,0.00001750317,0.03977872,0.0007880056,0.00006902143,0.00003377656,0.0004651841,0.0007051891,0.0002478983,0.0004980299,0.9571016,0.00008830982],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005947387,0.00003091888,0.00001224974,0.00005446429,0.00001606904,0.000007213237,0.9993244,0.00003769495,0.0004574648],"genre_scores_gemma":[0.0004763817,0.0001226004,0.0001326548,0.00005521143,0.000009617064,0.00003959236,0.9972096,0.00004177821,0.001912592],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0574321,"threshold_uncertainty_score":0.2188902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04116235066253105,"score_gpt":0.2526214914291837,"score_spread":0.2114591407666527,"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."}}