{"id":"W2952450976","doi":"10.1111/1911-3846.12544","title":"Income Smoothing and the Usefulness of Earnings for Monitoring in Debt Contracting","year":2019,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Smoothing; Debt; Loan; Economics; Net income; Credit risk; Econometrics; Monetary economics; Labour economics; Business; Actuarial science; Finance; 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":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01156831,0.0002406538,0.0005274558,0.0006215124,0.0004869175,0.0006501924,0.0007547652,0.0001106663,0.00003003639],"category_scores_gemma":[0.02391303,0.0002013616,0.00009916604,0.001053496,0.0003069966,0.002568315,0.0009266855,0.0009215327,0.00004520477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006592611,"about_ca_system_score_gemma":0.00007471328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002685809,"about_ca_topic_score_gemma":0.00003305008,"domain_scores_codex":[0.9970459,0.0001088065,0.0007097117,0.0005753118,0.0008613385,0.0006988941],"domain_scores_gemma":[0.9905646,0.002740628,0.005640542,0.0004428787,0.000594641,0.00001665747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003929151,0.00002734678,0.9716242,0.00101411,0.00003355168,0.000005951159,0.0005783478,0.00009362183,0.0009171055,0.01375724,0.000140545,0.01141509],"study_design_scores_gemma":[0.0121958,0.00004878698,0.8859187,0.003340236,0.00003068392,0.000003237019,0.009504681,0.01489963,0.000792117,0.006101381,0.06637218,0.0007925426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841582,0.0004896732,0.001604972,0.001096829,0.0003654314,0.001620287,0.000001617123,0.00007420831,0.01058883],"genre_scores_gemma":[0.9980701,0.00001620921,0.0001321087,0.0001235589,0.0007059773,0.0001417898,0.000005194036,0.00006824902,0.0007367888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08570545,"threshold_uncertainty_score":0.984309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04164234055889012,"score_gpt":0.2937407318379046,"score_spread":0.2520983912790145,"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."}}