{"id":"W6901404798","doi":"10.6068/dp14ba8e3ac5a19","title":"Trend 2001 - 2004. 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, Water transportation, Network and/or information security technology | Units: %, 2001-2004. 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":"Business statistics; Official statistics; Economic statistics; The Internet; Government (linguistics); Information technology; Information and Communications Technology; Census; Summary statistics; Descriptive 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":[0.00201441,0.002465656,0.002709057,0.01011077,0.003651867,0.004847721,0.005398086,0.001531537,0.06945962],"category_scores_gemma":[0.01840868,0.001670477,0.002110745,0.04568282,0.0006291461,0.002471513,0.002379054,0.003284166,0.04216762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05400398,"about_ca_system_score_gemma":0.1453366,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9942513,"about_ca_topic_score_gemma":0.9926684,"domain_scores_codex":[0.9952155,0.0002684095,0.0005108038,0.0005293984,0.002407834,0.001067985],"domain_scores_gemma":[0.9564296,0.001367588,0.001319337,0.0009407285,0.03822299,0.001719711],"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":[0.00002214824,0.000007760719,0.001316532,0.0002539182,0.00002119704,0.000006697378,0.00002152259,0.0001016195,0.000007332127,0.0003158523,0.996551,0.001374333],"study_design_scores_gemma":[0.0001589513,0.00001608045,0.0415899,0.0009960975,0.00009281306,0.00002925839,0.0007274363,0.0005462965,0.0002060894,0.0005566535,0.9549864,0.0000940402],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006870826,0.00004614038,0.00001844866,0.0001194582,0.00002814478,0.00001490426,0.9989771,0.00003945286,0.0006877191],"genre_scores_gemma":[0.0008162645,0.0002449605,0.0002452719,0.0001267438,0.00001888455,0.0001132172,0.9945471,0.00006146985,0.003825961],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06945962,"threshold_uncertainty_score":0.3918282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03593688150879452,"score_gpt":0.2459315182494056,"score_spread":0.2099946367406111,"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."}}