{"id":"W6920220396","doi":"10.6068/dp14ba8cc7ee378","title":"Trend 2000 - 2007. Statistics Canada. CANSIM: Information and Communications Technology - Business and Government Internet Use | Country: Canada | Table: Survey of electronic commerce and technology, use of information and communication technologies, by North American Industry Classification System (NAICS) | Variable: Enterprises that are presently using it, Waste management and remediation services, Extranet | Units: %, 2000-2007. 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":"Economic statistics; Business statistics; Official statistics; The Internet; Government (linguistics); Information and Communications Technology; Census; Information 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007461595,0.0006135227,0.0009246271,0.0004615549,0.0001802431,0.0003477246,0.00153525,0.0006800991,0.00001253924],"category_scores_gemma":[0.0002008448,0.0006523366,1.447552e-7,0.001326757,0.001191853,0.001816112,0.002013576,0.0009841821,8.695915e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008273431,"about_ca_system_score_gemma":0.002623063,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9967566,"about_ca_topic_score_gemma":0.9951824,"domain_scores_codex":[0.9962586,0.0004791692,0.001336334,0.0005750968,0.0008379619,0.0005128612],"domain_scores_gemma":[0.9924599,0.0005942319,0.003206906,0.003187832,0.0003797406,0.0001714048],"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":[0.0001290311,0.00005611383,0.01339502,0.001702467,0.0003305283,0.000002704512,0.00001112764,0.00002214845,0.000003584746,0.000311343,0.9831719,0.0008640147],"study_design_scores_gemma":[0.000849255,0.00006847141,0.001402212,0.0002793115,0.0004921575,0.00009655437,0.005293283,0.02847211,1.723088e-7,1.349272e-7,0.9625369,0.0005094727],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003094352,0.004432801,0.00007744769,0.00001738011,0.00005637571,0.00134715,0.9935741,0.0001181524,0.00006713336],"genre_scores_gemma":[0.005465866,0.01470472,0.0007888047,0.00005096216,0.000005395212,0.00004441743,0.9787994,0.000092257,0.00004815977],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02844996,"threshold_uncertainty_score":0.9995928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03179823956501483,"score_gpt":0.2391759471068597,"score_spread":0.2073777075418449,"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."}}