{"id":"W6901727708","doi":"10.6068/dp14ba8a7e10e84","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 labour remuneration, Total all stores, Home electronics and appliance 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; Financial services; Index (typography); 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":[0.001516347,0.002695548,0.002623398,0.008465244,0.002354561,0.004467082,0.005145788,0.001245703,0.0643915],"category_scores_gemma":[0.0119617,0.00158746,0.00192382,0.04272809,0.000561862,0.002478855,0.001936073,0.002813535,0.06277546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03099279,"about_ca_system_score_gemma":0.07645733,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9892675,"about_ca_topic_score_gemma":0.9865284,"domain_scores_codex":[0.9963707,0.0001884137,0.0003797522,0.0005294872,0.001716999,0.0008147249],"domain_scores_gemma":[0.9744403,0.0007332988,0.0009341489,0.0007223177,0.02217836,0.0009915052],"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":[0.00002859443,0.000007395857,0.001307103,0.0002106766,0.00002141569,0.000008131045,0.00001471308,0.0001135409,0.00001055217,0.0002352411,0.9967513,0.001291211],"study_design_scores_gemma":[0.0002021712,0.00001724122,0.03907006,0.000831481,0.00006797153,0.00003288425,0.0004847167,0.0006514752,0.0002422048,0.0005046251,0.9578068,0.00008843964],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005856283,0.00003151221,0.00001311789,0.0000554686,0.00001703143,0.000008190534,0.9992628,0.00003734634,0.0005161079],"genre_scores_gemma":[0.0004976323,0.0001380764,0.000150735,0.00006030139,0.000010573,0.0000480606,0.9966808,0.00004903535,0.002364706],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0643915,"threshold_uncertainty_score":0.2248695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02550051194949233,"score_gpt":0.2329246202227218,"score_spread":0.2074241082732295,"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."}}