{"id":"W6901619443","doi":"10.6068/dp14ba8e5bae132","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, Computer systems design and related services, E-mail (electronic mail) | 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":"Business statistics; Official statistics; Economic statistics; The Internet; Government (linguistics); Information and Communications Technology; Census; Information technology; Telephone number; 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":[0.001884241,0.002240737,0.002626796,0.009925138,0.00332451,0.004423776,0.004897333,0.001417949,0.05428816],"category_scores_gemma":[0.01667647,0.001476827,0.002066266,0.04375384,0.0006111221,0.002239935,0.002342035,0.00306867,0.03616114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04745549,"about_ca_system_score_gemma":0.1338506,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938606,"about_ca_topic_score_gemma":0.9929743,"domain_scores_codex":[0.9957761,0.000233215,0.0004374972,0.0004975242,0.00208815,0.0009674997],"domain_scores_gemma":[0.9629148,0.001128508,0.001219837,0.0008351001,0.03230269,0.001598984],"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":[0.00002317593,0.000008470044,0.001743683,0.000255464,0.00002463414,0.000006945251,0.00002393899,0.0001035802,0.000008132949,0.000333988,0.9960163,0.001451528],"study_design_scores_gemma":[0.0001716461,0.00001860595,0.05131714,0.001018945,0.0001054753,0.00003238175,0.0008434518,0.0006233813,0.0002189957,0.0005865691,0.9449623,0.000101161],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000860605,0.00005118531,0.00001950656,0.000115513,0.00002620455,0.00001441427,0.9990043,0.00003958294,0.0006432711],"genre_scores_gemma":[0.0008939364,0.0002296087,0.0002463988,0.0001191233,0.00001791129,0.0001003423,0.9952631,0.00005139254,0.003078213],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05428816,"threshold_uncertainty_score":0.3443153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0306626276318012,"score_gpt":0.233422167770836,"score_spread":0.2027595401390348,"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."}}