{"id":"W6957891362","doi":"10.6068/dp14ba864879295","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, Computer and software 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Retail trade; Economic statistics; Summary statistics; Retail sales; Index (typography); Goods and services; Financial services; Publication","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":[0.001569495,0.00276718,0.002693643,0.00899622,0.002452376,0.004750357,0.005413833,0.001281092,0.0698498],"category_scores_gemma":[0.01311776,0.001618565,0.001848728,0.04353795,0.0005943595,0.002664015,0.001983329,0.002843294,0.06814517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0320305,"about_ca_system_score_gemma":0.07911775,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.9883233,"about_ca_topic_score_gemma":0.9853874,"domain_scores_codex":[0.9962242,0.0001949403,0.0003715621,0.0005437367,0.001799866,0.000865605],"domain_scores_gemma":[0.9709226,0.0008751571,0.001076897,0.0008474963,0.0250796,0.001198273],"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":[0.00002713725,0.000007319476,0.001274827,0.0001834307,0.00001967523,0.000007337745,0.00001421461,0.0001129844,0.000009503882,0.0002334194,0.9968638,0.001246273],"study_design_scores_gemma":[0.0001858226,0.00001715965,0.03554099,0.0007620918,0.00006277776,0.00003012659,0.0004571594,0.0006673353,0.0002264194,0.0005289114,0.9614342,0.00008683207],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.00005996106,0.00002751581,0.00001483977,0.0000569246,0.00001647786,0.000008604623,0.9992211,0.00004455001,0.0005499511],"genre_scores_gemma":[0.0004840009,0.0001221814,0.0001543194,0.00005840902,0.00001013333,0.00004897054,0.99674,0.00005455192,0.002327378],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9883233,"threshold_uncertainty_score":0.2336709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03125575254894102,"score_gpt":0.2357905867780968,"score_spread":0.2045348342291558,"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."}}