{"id":"W6958037184","doi":"10.6068/dp14ba8d9c3cb78","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 the Internet that do not buy, Miscellaneous wholesaler-distributors, 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":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"The Internet; Business statistics; Official statistics; Government (linguistics); Economic statistics; Census; Information and Communications Technology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004101345,0.0004308771,0.0006570336,0.0001314177,0.0001401112,0.0002244723,0.002895154,0.0003051382,0.00001583812],"category_scores_gemma":[0.0001101129,0.0004107013,2.746092e-7,0.001258568,0.0006161293,0.0001929809,0.001398234,0.0009342695,0.000001663103],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006971654,"about_ca_system_score_gemma":0.008838291,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996098,"about_ca_topic_score_gemma":0.9923614,"domain_scores_codex":[0.9971712,0.0003048563,0.0007313503,0.0006337259,0.000669761,0.0004891386],"domain_scores_gemma":[0.99478,0.0006038782,0.001297023,0.002752867,0.0002857046,0.0002805301],"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":[0.00003052366,0.00003653729,0.001793296,0.0001396591,0.0001509862,0.000001731699,0.000006012973,0.00005236065,0.000002456545,0.006530796,0.9907294,0.0005262378],"study_design_scores_gemma":[0.0003016206,0.00005984925,0.000751741,0.00004772626,0.0001148251,0.00005901709,0.0004268021,0.01445994,1.995929e-7,3.299768e-7,0.9833945,0.0003834243],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008555452,0.0004389898,0.0003310477,0.0000881378,0.00007802525,0.0006366876,0.9981233,0.00004791726,0.0001703383],"genre_scores_gemma":[0.0320122,0.0004374806,0.0001455961,0.0002311035,0.000008509182,0.00003276897,0.9668108,0.00004877391,0.0002727855],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03192665,"threshold_uncertainty_score":0.9998345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01788215105038105,"score_gpt":0.2260826684409558,"score_spread":0.2082005173905748,"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."}}