{"id":"W4392121664","doi":"10.3390/jrfm17030094","title":"Bibliometric Framing of Research Trends Regarding Public Sector Auditing to Fight Corruption and Prevent Fraud","year":2024,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Language change; Audit; Public sector; Framing (construction); Accounting; Analytics; Business; Public institution; Public relations; Political science; Law; Engineering; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.004506859,0.00006840684,0.000172115,0.01668835,0.0003318279,0.000263577,0.0001161117,0.00005065949,0.0001307086],"category_scores_gemma":[0.0004762772,0.00006226049,0.00005639822,0.0118848,0.00005886815,0.000288153,0.0001275256,0.0002148175,0.00000617395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001814839,"about_ca_system_score_gemma":0.00008616808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009101049,"about_ca_topic_score_gemma":0.0001356135,"domain_scores_codex":[0.9986764,0.0001159252,0.0003861838,0.0001574479,0.000424913,0.0002391572],"domain_scores_gemma":[0.9993238,0.0001826512,0.0001489961,0.0000570454,0.0001390778,0.0001484253],"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":[0.00001676923,0.00002604342,0.005754679,0.0000681221,0.00001677486,0.00001707856,0.004462338,0.000007466298,0.000008013,0.008302385,0.001929757,0.9793906],"study_design_scores_gemma":[0.0002212416,0.0001145854,0.1984336,0.0003425793,0.00002508088,0.000004353999,0.003442397,0.00007902752,0.000007851361,0.001015241,0.7962161,0.00009789462],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9720688,0.002766295,0.01023212,0.001496483,0.001441287,0.0001804508,0.000006833276,0.00001933571,0.01178835],"genre_scores_gemma":[0.9887657,0.008125078,0.001128463,0.00003293218,0.0003923817,0.000004720224,4.859564e-7,0.000006011111,0.001544233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9792927,"threshold_uncertainty_score":0.9944566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05778465782098792,"score_gpt":0.350770709879381,"score_spread":0.2929860520583931,"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."}}