{"id":"W6920385559","doi":"10.6068/dp14ba866544d62","title":"Trend 2007 - 2009. Statistics Canada. CANSIM: Business, Consumer and Property Services - Professional, Scientific and Technical Services | Country: Canada | Table: Advertising and related services, operating expenses, by North American Industry Classification System (NAICS) | Variable: Rental and leasing, Direct mail advertising | Units: %, 2007-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-013.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Official statistics; Economic statistics; Census; Publication; Socioeconomic status; Renting; Service (business); Financial services; 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":[0.001988938,0.002540044,0.002859479,0.009348826,0.003252576,0.005356844,0.005467447,0.00165187,0.09361948],"category_scores_gemma":[0.02110037,0.001727343,0.002125246,0.04499088,0.0006971097,0.002889979,0.002358012,0.003312763,0.07181081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04510877,"about_ca_system_score_gemma":0.1251352,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9911572,"about_ca_topic_score_gemma":0.9890599,"domain_scores_codex":[0.9956214,0.0002695468,0.0004821933,0.0006311882,0.002012949,0.0009826929],"domain_scores_gemma":[0.9631433,0.001412627,0.001064549,0.00123519,0.03158183,0.001562408],"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":[0.00001629101,0.000004271898,0.000645606,0.000166662,0.00001439809,0.000005199288,0.00001317589,0.00007859257,0.000007212235,0.0002867584,0.9977438,0.001017986],"study_design_scores_gemma":[0.00012726,0.000008601373,0.01414154,0.0007627313,0.00005545671,0.00002326627,0.0003487471,0.0004150877,0.0001493518,0.0006834521,0.9832138,0.00007083226],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000340177,0.00003930791,0.00001926505,0.0001015191,0.00002552663,0.000009753831,0.9990516,0.00004915953,0.000669802],"genre_scores_gemma":[0.0004863121,0.0001966828,0.0002672117,0.0001169016,0.00001618208,0.0000837847,0.9961644,0.00009092272,0.002577577],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09361948,"threshold_uncertainty_score":0.3272885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663314254487535,"score_gpt":0.2430412701320184,"score_spread":0.226408127587143,"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."}}