{"id":"W6901797567","doi":"10.6068/dp14ba813bf308","title":"Trend 1966 - 1997. Statistics Canada. CANSIM: Retail and Wholesale - Retail Sales by Type of Store | Country: Canada | Table: Direct selling, by method of sale and commodity | Variable: All other merchandise, Sales by mail | Units: $CAD x 1,000, 1966-1997. 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":"Economic statistics; Commodity; Census; Retail trade; Retail sales; Summary statistics; 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":[0.00145397,0.002469235,0.002403534,0.008888498,0.00235191,0.00406645,0.004904954,0.001241248,0.07451867],"category_scores_gemma":[0.01304512,0.00142171,0.001541513,0.04140886,0.0006301744,0.002289283,0.001824687,0.002646602,0.06547115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03222408,"about_ca_system_score_gemma":0.0771465,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9891651,"about_ca_topic_score_gemma":0.9856628,"domain_scores_codex":[0.9965243,0.0001736151,0.0003520362,0.0005315086,0.001601218,0.0008174119],"domain_scores_gemma":[0.975817,0.0008569746,0.001022424,0.0008048773,0.02036943,0.001129278],"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":[0.00002289855,0.000006264816,0.001121337,0.0001801092,0.00001673881,0.000007590483,0.00001629095,0.0001358789,0.000009439504,0.0003186491,0.996895,0.001269802],"study_design_scores_gemma":[0.0001332706,0.00001192294,0.02579424,0.0006086619,0.00004587139,0.0000263137,0.0003799205,0.0005097111,0.0001806958,0.0005251143,0.9717146,0.00006969304],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005080579,0.0000289319,0.00001524908,0.00005203314,0.00001362377,0.00000717846,0.9992599,0.00004129406,0.0005309288],"genre_scores_gemma":[0.0005584632,0.0001390822,0.0001708422,0.00005106966,0.000009268864,0.00004740373,0.9966871,0.00005604482,0.002280714],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07451867,"threshold_uncertainty_score":0.2492898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04522225744064751,"score_gpt":0.274950165831878,"score_spread":0.2297279083912305,"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."}}