{"id":"W4236303889","doi":"10.2139/ssrn.1326104","title":"Reversal of Abnormal Accruals: Detection, Economic Consequences and Determinants","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Accrual; Economics; Business; Accounting; Earnings","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005440008,0.000388993,0.0006962396,0.001660831,0.0002421652,0.00209551,0.0006722151,0.001149768,0.003503786],"category_scores_gemma":[0.06137246,0.0002074958,0.0004343538,0.0008052303,0.001260396,0.001698508,0.0005707213,0.001389284,0.000478279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004416517,"about_ca_system_score_gemma":0.0007988753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005193148,"about_ca_topic_score_gemma":0.000276449,"domain_scores_codex":[0.9984451,0.00051719,0.0001525941,0.0001668064,0.0005746396,0.0001437429],"domain_scores_gemma":[0.9352663,0.03926659,0.01568821,0.004523928,0.003844365,0.001410639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003396471,0.001299627,0.80573,0.000116906,0.0001416066,0.0009680269,0.0001597477,0.00850446,0.005651407,0.02983521,0.00144242,0.1427541],"study_design_scores_gemma":[0.0003774243,0.002792296,0.7326642,0.00007640234,0.0002539682,0.005307862,0.0003817389,0.1360015,0.0173633,0.1025045,0.002174223,0.000102588],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828851,0.0004033034,0.01184128,0.0007556051,0.00003993538,0.00005558916,0.0001551497,0.0001355433,0.003728446],"genre_scores_gemma":[0.9977962,0.0001010818,0.001488803,0.00002979827,0.00003280969,0.000005194267,0.00005615226,0.000007701085,0.0004821963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005440008,"threshold_uncertainty_score":0.02876985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02556504043991828,"score_gpt":0.3301935340347538,"score_spread":0.3046284935948356,"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."}}