{"id":"W6958013078","doi":"10.6068/dp14ba8ecfd2813","title":"Trend 2000 - 2006. 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 Internet who do not use electronic commerce, Health care and social assistance public, Customers are not ready | Units: %, 2000-2006. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-125.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Diverse Cultural and Historical Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"The Internet; Government (linguistics); Official statistics; Business statistics; Economic statistics; Information and Communications Technology; Information technology; Telephone number; Census","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":[0.002052555,0.002474907,0.002764397,0.009822154,0.003434355,0.004483283,0.005352087,0.001530653,0.06208804],"category_scores_gemma":[0.01838813,0.001621624,0.002282293,0.04456607,0.0006130309,0.002405711,0.002394774,0.003279049,0.03887079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04900897,"about_ca_system_score_gemma":0.1402358,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9939996,"about_ca_topic_score_gemma":0.9926783,"domain_scores_codex":[0.9956008,0.0002522522,0.0005047512,0.0005105328,0.002149916,0.0009817916],"domain_scores_gemma":[0.9623047,0.00120354,0.001281692,0.0008633107,0.03271008,0.001636681],"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":[0.00002269361,0.000008561878,0.00150611,0.0002745612,0.00002215855,0.000006286925,0.00002194154,0.000105669,0.000007276614,0.0003189793,0.9963028,0.001402905],"study_design_scores_gemma":[0.0001927439,0.00002028327,0.04775098,0.00118228,0.0001058651,0.00003408833,0.0007815124,0.0006664585,0.0002158345,0.0006509459,0.9482917,0.0001073837],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006784206,0.00004702466,0.0000177803,0.0001141132,0.0000265329,0.00001439693,0.9990768,0.00003891401,0.00059657],"genre_scores_gemma":[0.0008272558,0.0002508475,0.0002510581,0.0001316859,0.00001903596,0.0001097917,0.9952736,0.00005741576,0.003079387],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06208804,"threshold_uncertainty_score":0.3555866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03217153468405927,"score_gpt":0.258074758352107,"score_spread":0.2259032236680477,"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."}}