{"id":"W6975852691","doi":"10.6068/dp14ba8ada7f499","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, website features, by North American Industry Classification System (NAICS) and size of enterprise | Variable: Customised web site for repeat visitors, Construction, Large 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; The Internet; Official statistics; Economic statistics; Government (linguistics); Information and Communications Technology; Information technology; Descriptive statistics; Census; Telephone number","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":[0.002254534,0.002517199,0.002976743,0.009251797,0.003900673,0.005405239,0.005408608,0.001690468,0.08453863],"category_scores_gemma":[0.02238895,0.001698746,0.002169978,0.04988009,0.0007414254,0.002715714,0.002604405,0.003524699,0.05575419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05169527,"about_ca_system_score_gemma":0.1392074,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9930226,"about_ca_topic_score_gemma":0.9913748,"domain_scores_codex":[0.9946426,0.0002958706,0.0005509214,0.0006002272,0.002725383,0.001185035],"domain_scores_gemma":[0.9465223,0.001877186,0.001325324,0.001217037,0.04699995,0.00205814],"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":[0.00001951252,0.000007857941,0.0009532551,0.0002361027,0.00001636039,0.000005304849,0.0000190588,0.00008606823,0.000007213789,0.000220661,0.9973614,0.00106723],"study_design_scores_gemma":[0.0002020707,0.00001558137,0.03437863,0.0009774835,0.00008865301,0.00002488713,0.0007167474,0.0004071331,0.0001997253,0.0005360391,0.9623535,0.00009966527],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004719113,0.00003574819,0.00001369837,0.0001021811,0.00002009619,0.00001192082,0.9991831,0.0000363822,0.0005495942],"genre_scores_gemma":[0.0006433459,0.0001982249,0.0002421596,0.0001391152,0.00001731028,0.0001157642,0.9955285,0.00006466866,0.003050871],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08453863,"threshold_uncertainty_score":0.3750772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01712059172094234,"score_gpt":0.2316062016553659,"score_spread":0.2144856099344236,"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."}}