{"id":"W4380088402","doi":"10.1111/ijau.12323","title":"Auditors' interpretation of risk and the quality of analysts' earnings forecasts: Evidence from textual analysis of key audit matters","year":2023,"lang":"en","type":"article","venue":"International Journal of Auditing","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Audit; Earnings; Earnings quality; Accounting; Transparency (behavior); Business; Quality (philosophy); Key (lock); Litigation risk analysis; Emerging markets; Actuarial science; Accrual; Finance; Computer science; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003803159,0.0001773385,0.0007042738,0.001139468,0.00007839509,0.0001111988,0.0007698198,0.00005078669,0.000193905],"category_scores_gemma":[0.03375791,0.0001416234,0.0004580771,0.001346443,0.0002891133,0.001152438,0.0004203598,0.0002961259,0.00001014175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006638965,"about_ca_system_score_gemma":0.00003248778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003090472,"about_ca_topic_score_gemma":0.0002260817,"domain_scores_codex":[0.9964219,0.0001427768,0.001671143,0.0002318942,0.001359825,0.0001724353],"domain_scores_gemma":[0.9504346,0.00253472,0.04548889,0.0001883165,0.001337741,0.00001572541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001607949,0.00009392147,0.7958909,0.0002879008,0.008807715,0.00003532138,0.005930048,0.07440081,0.004601889,0.003055999,0.003805701,0.1014818],"study_design_scores_gemma":[0.001614654,0.00002864289,0.906637,0.00139362,0.002059955,0.000002765625,0.003963263,0.08107732,0.0004508478,0.001736114,0.0008195207,0.0002162758],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8963708,0.00009130653,0.1012801,0.001411611,0.000478403,0.00008596646,0.00005050203,0.00001682938,0.0002144162],"genre_scores_gemma":[0.9982489,0.0001710012,0.0004871846,0.0001638631,0.0008472842,0.000002745762,0.00002724879,0.00001735356,0.00003446405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1107461,"threshold_uncertainty_score":0.9743811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01446660854149035,"score_gpt":0.2746805986209744,"score_spread":0.260213990079484,"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."}}