{"id":"W6957788202","doi":"10.6068/dp14ba83cbcba23","title":"Trend 2008 - 2011. Statistics Canada. CANSIM: Retail and Wholesale - Retail Sales by Type of Store | Country: Canada | Table: Annual retail store survey, financial estimates by North American Industry Classification System (NAICS) and store type | Variable: Number of stores, Convenience stores, Chain stores | Units: , 2008-2011. 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":"Census; Economic statistics; Retail trade; Retail sales; Summary statistics; Index (typography); Financial services; Official statistics; Goods and 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":[0.001535284,0.002563729,0.002566354,0.008568719,0.002459605,0.004735744,0.005172681,0.001298578,0.07959147],"category_scores_gemma":[0.01323031,0.001568747,0.001906143,0.04179971,0.0005863265,0.002657249,0.001981902,0.002822136,0.07274617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03238366,"about_ca_system_score_gemma":0.08388774,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9897779,"about_ca_topic_score_gemma":0.9871652,"domain_scores_codex":[0.9964893,0.0001841906,0.0003229968,0.0004890889,0.001664091,0.000850313],"domain_scores_gemma":[0.9738385,0.0008558984,0.0008998414,0.0007695453,0.02248301,0.001153195],"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":[0.00002048121,0.00000565501,0.0009758628,0.0001665453,0.00001580594,0.000006426999,0.00001387899,0.00009581449,0.000007834188,0.0002345648,0.9972886,0.001168589],"study_design_scores_gemma":[0.0001613809,0.00001376671,0.02678014,0.0007393777,0.00005709503,0.00002884616,0.0004431144,0.0005939979,0.0001892507,0.0005490786,0.9703611,0.00008277164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005377484,0.00003056197,0.00001597549,0.00006642642,0.00001656901,0.000008258207,0.9991457,0.00004957543,0.0006131454],"genre_scores_gemma":[0.0005266219,0.0001470377,0.0002030907,0.00007371657,0.00001160652,0.00005632008,0.9961829,0.00007416632,0.002724529],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07959147,"threshold_uncertainty_score":0.26626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03459671616171601,"score_gpt":0.2544391764783843,"score_spread":0.2198424603166683,"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."}}