{"id":"W6957562738","doi":"10.6068/dp14ba8f33e6077","title":"Trend 2005 - 2007. Statistics Canada. CANSIM: Information and Communications Technology - Business and Government Internet Use | Country: Canada | Table: Survey of electronic commerce and technology, characteristics of Web sites, by North American Industry Classification System (NAICS) | Variable: Enterprises offering information about organization's products or services, Advertising, public relations, and related services | Units: %, 2005-2007. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-125.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business statistics; Official statistics; The Internet; Economic statistics; Government (linguistics); Information and Communications Technology; Census; Information technology; Telephone number","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":[0.00216439,0.002453096,0.002851017,0.01047358,0.003468661,0.004847774,0.005389588,0.001450687,0.0634466],"category_scores_gemma":[0.01923416,0.001666839,0.002118033,0.04890813,0.0006536975,0.00249133,0.002437361,0.003226744,0.04154818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05257894,"about_ca_system_score_gemma":0.146905,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938681,"about_ca_topic_score_gemma":0.9920231,"domain_scores_codex":[0.9950558,0.0002800081,0.0005435371,0.0005420047,0.002484592,0.001094091],"domain_scores_gemma":[0.9569352,0.001419197,0.001342256,0.0009652147,0.03756609,0.001771997],"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":[0.00002090355,0.000007652528,0.001343047,0.000254973,0.00002186926,0.000006379527,0.00002151245,0.00009615401,0.000007185567,0.0003162233,0.9965016,0.001402461],"study_design_scores_gemma":[0.0001653989,0.00001729445,0.04112417,0.001101944,0.0001014027,0.00002948356,0.0007637209,0.0005552244,0.0002107064,0.0006221426,0.9552119,0.00009658505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006736126,0.00004839257,0.00001927721,0.0001153297,0.00002778225,0.00001502662,0.9990361,0.00004140681,0.0006292553],"genre_scores_gemma":[0.0007921492,0.0002478848,0.0002593093,0.0001316296,0.00001932869,0.0001117113,0.9951786,0.00006098762,0.003198412],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0634466,"threshold_uncertainty_score":0.3814887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01327115560170128,"score_gpt":0.2142720590242405,"score_spread":0.2010009034225393,"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."}}