{"id":"W6939234312","doi":"10.6068/dp14ba8efacad98","title":"Trend 2002 - 2004. Statistics Canada. CANSIM: Information and Communications Technology - Business and Government Internet Use | Country: Canada | Table: Survey of electronic commerce and technology, barriers to electronic commerce, by North American Industry Classification System (NAICS) | Variable: Users of the Internet that do not sell, Construction of buildings, Concern about competitors analyzing company information | Units: %, 2002-2004. 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":"The Internet; Competitor analysis; Business statistics; Official statistics; Government (linguistics); Economic statistics; Census; Information technology; Information and Communications Technology; Summary statistics","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":[0.002131692,0.002578285,0.002830427,0.01063079,0.003576792,0.005079991,0.005606367,0.001571529,0.0678582],"category_scores_gemma":[0.01983615,0.001748843,0.002179823,0.04806889,0.0006535156,0.002607809,0.002527877,0.003221789,0.04470978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05338008,"about_ca_system_score_gemma":0.1406141,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938498,"about_ca_topic_score_gemma":0.9923246,"domain_scores_codex":[0.9950697,0.0002700652,0.000543902,0.000554856,0.002473324,0.001088144],"domain_scores_gemma":[0.95272,0.001437765,0.001428741,0.00107431,0.04147128,0.001867869],"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":[0.00002272375,0.000008501979,0.00137719,0.0002506139,0.00002029182,0.000006489887,0.00002200934,0.00009600331,0.000007768579,0.0002819973,0.9965152,0.001391382],"study_design_scores_gemma":[0.0001709954,0.00001767336,0.04286377,0.001030162,0.00008963257,0.00002836499,0.0007828046,0.0005637868,0.0002149548,0.0005649194,0.9535763,0.00009662918],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006675903,0.00004140725,0.0000178517,0.0001095944,0.0000269107,0.00001537978,0.9990401,0.00004266575,0.0006393194],"genre_scores_gemma":[0.0007528414,0.0002170483,0.0002347969,0.0001202658,0.00001833276,0.0001180652,0.9949091,0.00006208821,0.003567372],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0678582,"threshold_uncertainty_score":0.3873013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01870082376761232,"score_gpt":0.2320803432730527,"score_spread":0.2133795195054404,"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."}}