{"id":"W6901707202","doi":"10.6068/dp14ba8bf555786","title":"Most Recent Data (2012). Statistics Canada. CANSIM: Information and Communications Technology - Business and Government Internet Use | Country: Canada | Table: Survey of digital technology and Internet use, type of Information and Communication Technology | Variable: Industry-specific software, Health care and social assistance, Small size enterprises | Units: %, 2012. 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; Economic statistics; Government (linguistics); Information and Communications Technology; Information technology; Descriptive statistics; Social statistics; Big data","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":[0.002567084,0.002618211,0.003027054,0.01019058,0.004343935,0.005386179,0.005425315,0.001751103,0.09808601],"category_scores_gemma":[0.02502359,0.001828287,0.002452887,0.051628,0.0007036338,0.002752331,0.002786833,0.003573539,0.05362808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06497069,"about_ca_system_score_gemma":0.1670177,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9954273,"about_ca_topic_score_gemma":0.993697,"domain_scores_codex":[0.9937836,0.0003236878,0.0006468088,0.0005910496,0.003298125,0.001356616],"domain_scores_gemma":[0.941196,0.001941723,0.001376178,0.001150986,0.05198251,0.002352697],"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":[0.00001975221,0.000007847569,0.000940003,0.0002981207,0.00001604829,0.000005542113,0.00002305121,0.00008454579,0.000007211539,0.0002512589,0.9969505,0.001396108],"study_design_scores_gemma":[0.0001894766,0.00001728111,0.03883614,0.001257556,0.00009731055,0.00002565657,0.0008111108,0.0003849834,0.0001883387,0.0005511594,0.9575287,0.0001124357],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005103411,0.00004780815,0.00001710643,0.0001331625,0.00002651572,0.00001705075,0.9988698,0.00004047948,0.000796891],"genre_scores_gemma":[0.0009543792,0.0003411794,0.0003836031,0.0002155776,0.00002422405,0.0001910318,0.9928349,0.00009754764,0.004957657],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09808601,"threshold_uncertainty_score":0.4713976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04167645046574982,"score_gpt":0.2577663656188049,"score_spread":0.2160899151530551,"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."}}