{"id":"W4412533196","doi":"10.5267/j.ijdns.2024.8.016","title":"Digital drivers of digital transformation in public sector organizations","year":2025,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Digital Economy and Transformation","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital transformation; Transformation (genetics); Public sector; Business; Computer science; Political science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003013165,0.00004834096,0.00008229029,0.0004355389,0.00004892808,0.0009605166,0.0006668229,0.00001512988,0.00001459929],"category_scores_gemma":[0.0001259829,0.0000431982,0.00001513501,0.0008614017,0.0001252338,0.02462057,0.0001250666,0.00005365288,0.000003301868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002303537,"about_ca_system_score_gemma":0.000106512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002977848,"about_ca_topic_score_gemma":0.00001371273,"domain_scores_codex":[0.9992574,0.000001188362,0.0003387028,0.00008190684,0.0002309064,0.00008982357],"domain_scores_gemma":[0.9992911,0.00002823869,0.0001852397,0.00007312218,0.0004123141,0.00001004879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000866254,0.0002246557,0.27555,0.00005137478,0.00008969568,0.000006638505,0.0002529759,0.001591939,0.00006422758,0.2186165,0.001348378,0.502117],"study_design_scores_gemma":[0.007378308,0.0001128263,0.2470016,0.001369501,0.0001206325,0.0001040194,0.003456532,0.1951174,0.0003852269,0.1006364,0.4434458,0.0008718409],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7706463,0.00008500391,0.07829808,0.005352859,0.001525137,0.0001718833,0.0001369938,0.0000194289,0.1437643],"genre_scores_gemma":[0.9995489,0.00002519365,0.00006821173,0.0001331,0.0001289893,2.146941e-7,0.00007959547,0.00000171536,0.000014062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5012451,"threshold_uncertainty_score":0.9890215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01681506560062709,"score_gpt":0.2388880720501187,"score_spread":0.2220730064494916,"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."}}