{"id":"W6957997691","doi":"10.6068/dp14ba8afffc348","title":"Trend 2000 - 2005. Statistics Canada. CANSIM: Information and Communications Technology - Business and Government Internet Use | Country: Canada | Table: Survey of electronic commerce and technology, characteristics of Web sites, by North American Industry Classification System (NAICS) | Variable: Enterprises offering digital products or services, Educational services public | Units: %, 2000-2005. 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; The Internet; Government (linguistics); Economic statistics; Telephone number; Information and Communications Technology; Census; Information technology","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":[0.002235442,0.002572146,0.002885447,0.01043939,0.003452657,0.004939103,0.005576011,0.001504156,0.06690814],"category_scores_gemma":[0.01956407,0.001709407,0.002143258,0.05047317,0.000648993,0.002748164,0.002450523,0.003275401,0.04468248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05202103,"about_ca_system_score_gemma":0.1448005,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938631,"about_ca_topic_score_gemma":0.9915646,"domain_scores_codex":[0.9950829,0.0002822458,0.0005243394,0.0005511395,0.002443537,0.001115942],"domain_scores_gemma":[0.9570329,0.001343847,0.001353569,0.001003659,0.03735326,0.00191271],"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":[0.00002279016,0.000007799206,0.001269802,0.0002624458,0.00002121553,0.000006680775,0.00002332703,0.0001012567,0.000007492595,0.0003213361,0.9964914,0.001464521],"study_design_scores_gemma":[0.0001658291,0.00001753501,0.03804791,0.001063584,0.00009288944,0.00002842963,0.0007495476,0.0005479299,0.0001992397,0.0006409102,0.9583489,0.00009728576],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006228535,0.00004198523,0.00001993674,0.0001086338,0.00002579295,0.00001522479,0.9990442,0.00004546476,0.0006364911],"genre_scores_gemma":[0.0007552695,0.0002268859,0.0002844589,0.0001323809,0.00001823132,0.0001211642,0.9951161,0.00007166594,0.003273814],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06690814,"threshold_uncertainty_score":0.3774408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216405936949524,"score_gpt":0.2314546992703697,"score_spread":0.2092906399008745,"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."}}