{"id":"W6920511941","doi":"10.6068/dp14ba8a5fbb025","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, main benefits of Information and Communication Technology | Variable: Reduced transaction times, Couriers and messengers, 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; The Internet; Official statistics; Economic statistics; Government (linguistics); Information and Communications Technology; Information technology; Descriptive statistics; Database transaction","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009084607,0.0006195094,0.0009892421,0.0005490274,0.0001069995,0.000408167,0.002073004,0.000823414,0.00008906353],"category_scores_gemma":[0.001231683,0.0006545972,9.720959e-8,0.001164274,0.001474811,0.003954889,0.003225,0.0008025204,0.000002414803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003096425,"about_ca_system_score_gemma":0.004436488,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9923751,"about_ca_topic_score_gemma":0.9882672,"domain_scores_codex":[0.9964821,0.0003011046,0.001437262,0.0006528909,0.0006674962,0.0004591927],"domain_scores_gemma":[0.9920093,0.0008480257,0.001832409,0.004320311,0.0007510512,0.0002388386],"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":[0.0002527327,0.00006905924,0.0003374503,0.0005055057,0.0004483587,0.000004383086,0.000009527103,0.000007166211,0.00001100369,0.001152257,0.9952907,0.001911858],"study_design_scores_gemma":[0.001189244,0.0001123224,0.0001067568,0.0001645797,0.0004242656,0.0004028857,0.0006307157,0.006589865,5.042812e-7,0.000001063535,0.98983,0.0005478194],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005903301,0.006082776,0.0001505597,0.00004949792,0.0001013857,0.001016962,0.992354,0.00008752558,0.00009824905],"genre_scores_gemma":[0.00116827,0.02234545,0.001026037,0.00005283883,0.000004757943,0.00002371156,0.9751661,0.0001036975,0.0001091088],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01718788,"threshold_uncertainty_score":0.9995905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02483550035628047,"score_gpt":0.235411043872027,"score_spread":0.2105755435157466,"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."}}