{"id":"W6958115368","doi":"10.6068/dp14ba89ab9cd17","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, capital expenditures on types of Information and Communication Technologies | Variable: Finance and insurance, Medium size enterprises, Off-the-shelf software | 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":"Biomedical and Chemical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business statistics; Economic statistics; The Internet; Official statistics; Descriptive statistics; Government (linguistics); Information and Communications Technology; Information technology; Publication; Census","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":[0.002162218,0.002555867,0.00300459,0.009556754,0.003699493,0.005289288,0.005125198,0.001737255,0.09236825],"category_scores_gemma":[0.0214472,0.001735205,0.002184022,0.05108577,0.0006807665,0.002677739,0.002585121,0.003488814,0.05710866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05417667,"about_ca_system_score_gemma":0.1433941,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9936795,"about_ca_topic_score_gemma":0.9914368,"domain_scores_codex":[0.9944238,0.0002784149,0.000551045,0.00056728,0.002954043,0.001225526],"domain_scores_gemma":[0.9492773,0.001722054,0.001311932,0.001064903,0.04460523,0.002018569],"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":[0.00001724287,0.000007823482,0.000895082,0.000251329,0.00001506265,0.000005365674,0.00001874441,0.00008622051,0.000006923214,0.0002398381,0.997282,0.001174235],"study_design_scores_gemma":[0.0001817229,0.00001507153,0.03382103,0.001075546,0.00008313362,0.00002425916,0.0006709656,0.0004083577,0.0001941564,0.0005313937,0.9628949,0.0000995937],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004559963,0.00004047589,0.0000144583,0.0001107996,0.0000207233,0.00001273995,0.9990329,0.00003649146,0.0006858862],"genre_scores_gemma":[0.0007666704,0.0002745808,0.000296611,0.0001675457,0.0000200989,0.0001380182,0.9941396,0.00007986428,0.004117091],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09236825,"threshold_uncertainty_score":0.3930811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02381094542553924,"score_gpt":0.2514728844191768,"score_spread":0.2276619389936376,"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."}}