{"id":"W2964513510","doi":"10.1111/abac.12165","title":"Audit Adjustments and Public Sector Audit Quality","year":2019,"lang":"en","type":"article","venue":"Abacus","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; Queen's University","keywords":"Joint audit; Accounting; Audit; Business; Chief audit executive; Quality audit; Audit plan; Performance audit; Earnings management; Audit evidence; Public sector; Information technology audit; External auditor; Context (archaeology); Austerity; Earnings; Internal audit; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.01659564,0.0001301812,0.0004535014,0.001994677,0.0009008466,0.006113973,0.0005550309,0.0009012737,0.00379098],"category_scores_gemma":[0.1386647,0.0003375774,0.00050874,0.004020788,0.002586144,0.002713796,0.002611197,0.001677444,0.000380625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01506232,"about_ca_system_score_gemma":0.006561908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0845509,"about_ca_topic_score_gemma":0.09417561,"domain_scores_codex":[0.9793165,0.00713117,0.002572868,0.001405398,0.006158561,0.00341546],"domain_scores_gemma":[0.7225053,0.04055398,0.1987945,0.007828246,0.02272076,0.007597156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004292199,0.0001328256,0.9337627,0.0002479692,0.0001790021,0.0002661915,0.006662756,0.004338878,0.0008468337,0.007598766,0.003194174,0.04234072],"study_design_scores_gemma":[0.00002749957,0.0001399829,0.9884162,0.0001156548,0.00002893607,0.0001159044,0.002262686,0.0009633125,0.0002623507,0.00128316,0.006350778,0.00003342686],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774525,0.00268173,0.0009440211,0.00843585,0.00009563151,0.00006480941,0.0003690628,0.00004525613,0.009911029],"genre_scores_gemma":[0.9985394,0.0001900726,0.0001045635,0.0001715261,0.00003299063,0.000004704445,0.0000651754,0.00000509196,0.0008864577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0845509,"threshold_uncertainty_score":0.1681175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01792357654784648,"score_gpt":0.2305644832132971,"score_spread":0.2126409066654506,"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."}}