{"id":"W6920365636","doi":"10.6068/dp14ba8affe4d47","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: Online payment, Transportation equipment manufacturing, Total, all 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; Census; Information technology; Descriptive statistics; 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":[0.002392513,0.002541197,0.002997033,0.00930148,0.003993778,0.005412567,0.005612372,0.001729873,0.08827641],"category_scores_gemma":[0.02352794,0.00170602,0.002239272,0.05030502,0.0007260269,0.002757384,0.002656576,0.003605696,0.0555863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05393731,"about_ca_system_score_gemma":0.1443153,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9932104,"about_ca_topic_score_gemma":0.9913611,"domain_scores_codex":[0.9943491,0.0003210125,0.0005896288,0.0006103714,0.002905349,0.001224702],"domain_scores_gemma":[0.9428168,0.002000483,0.001376825,0.00123347,0.05045955,0.002112945],"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":[0.00002020761,0.000008054414,0.0009314077,0.0002600777,0.00001702172,0.000005561095,0.00001978317,0.0000902249,0.000007585937,0.0002390368,0.9972731,0.001127864],"study_design_scores_gemma":[0.0002106522,0.00001578567,0.0335513,0.001061591,0.00009183611,0.00002503981,0.0007248198,0.0004178415,0.0002006055,0.0005592255,0.9630395,0.0001019452],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004522145,0.00003820126,0.0000142973,0.0001074714,0.00002070239,0.00001261126,0.9991437,0.0000350723,0.0005827852],"genre_scores_gemma":[0.0006694971,0.0002180784,0.0002707089,0.0001498519,0.00001804866,0.000126937,0.9953062,0.00006766612,0.003172902],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08827641,"threshold_uncertainty_score":0.3913444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02807305043250594,"score_gpt":0.2437115154433187,"score_spread":0.2156384650108127,"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."}}