{"id":"W6894091844","doi":"10.5281/zenodo.7777412","title":"GOVERNMENT DIGITALIZATION: EVALUATING EFFECTIVENESS AND RISKS FROM PUBLIC PERSPECTIVE","year":2023,"lang":"en","type":"preprint","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Digital Economy and Transformation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Quality (philosophy); Digital government; State (computer science); Corporate governance; Digital transformation; Perspective (graphical); Quarter (Canadian coin)","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":[0.02688134,0.0006084666,0.0005103708,0.003875785,0.001533795,0.004044542,0.0005649824,0.00113109,0.003239526],"category_scores_gemma":[0.04735687,0.0002766404,0.001482621,0.002680247,0.003554902,0.00482006,0.004109114,0.001199053,0.0003613218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003591529,"about_ca_system_score_gemma":0.002422723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001851232,"about_ca_topic_score_gemma":0.001630832,"domain_scores_codex":[0.9680367,0.01803978,0.002073831,0.0009287156,0.009256284,0.001664748],"domain_scores_gemma":[0.9149906,0.05203957,0.01827028,0.003912114,0.008967434,0.001820062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007818356,0.002256092,0.8027695,0.001037251,0.0004414284,0.0004673458,0.03433703,0.004607901,0.002017734,0.01358989,0.0008398197,0.1368541],"study_design_scores_gemma":[0.00008563924,0.005573013,0.8337817,0.0007276826,0.0005872134,0.00032373,0.1286653,0.00718695,0.007561991,0.006494117,0.008833304,0.0001793456],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795095,0.0002433173,0.002034887,0.0005144824,0.00001391032,0.0002284676,0.0001042165,0.00002210585,0.01732913],"genre_scores_gemma":[0.9985267,0.0001523133,0.0008223433,0.0000376187,0.000009768045,0.0001089896,0.00004535051,0.000003610288,0.0002932673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02688134,"threshold_uncertainty_score":0.1421638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1125949831143181,"score_gpt":0.2850007572130703,"score_spread":0.1724057740987521,"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."}}