{"id":"W6958035404","doi":"10.6068/dp14ba88a3a5a40","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, Computer and software 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; Index (typography); Goods and services; Financial services; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001451902,0.001504919,0.001978784,0.0001755027,0.0004640463,0.0004665346,0.001645939,0.0009306021,0.0002106157],"category_scores_gemma":[0.0007307163,0.001328037,6.81291e-7,0.0008974403,0.001288563,0.0004612438,0.0006377232,0.002192939,0.000006502445],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007367684,"about_ca_system_score_gemma":0.01206427,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9972605,"about_ca_topic_score_gemma":0.9941583,"domain_scores_codex":[0.9915289,0.001779971,0.001406873,0.002158455,0.001965592,0.001160155],"domain_scores_gemma":[0.9917964,0.002323318,0.001834756,0.002831483,0.000301264,0.0009127349],"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":[0.0005520172,0.0001350731,0.003126882,0.0008075985,0.0003927976,0.0002266357,0.00002183997,0.000126872,0.00001130368,0.00006017364,0.9942281,0.0003107559],"study_design_scores_gemma":[0.001110372,0.0006128169,0.001093721,0.0002023724,0.0005727913,0.0002011695,0.0008328176,0.02231524,6.030574e-8,1.245029e-8,0.9716795,0.001379148],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004484768,0.006644083,0.00001544448,0.00000689127,0.0005338972,0.001154854,0.990988,0.0001562888,0.00005206636],"genre_scores_gemma":[0.001542036,0.0002529168,0.0004624715,0.0002072946,0.0002477557,0.00002955076,0.9963183,0.0005561886,0.0003834871],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02254857,"threshold_uncertainty_score":0.99977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03492580574867302,"score_gpt":0.2404922644016791,"score_spread":0.2055664586530061,"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."}}