{"id":"W1709677996","doi":"10.1111/j.1467-629x.2012.00486.x","title":"The usefulness of operating cash flow and accrual components in improving the predictive ability of earnings: a re-examination and extension","year":2012,"lang":"en","type":"article","venue":"Accounting and Finance","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Cash flow; Accrual; Operating cash flow; Profitability index; Econometrics; Earnings; Cash flow forecasting; Business; Cash flow statement; Panel data; Economics; Accounting; Finance","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":[],"consensus_categories":[],"category_scores_codex":[0.002535897,0.0001474755,0.0002104719,0.0000621565,0.0004401164,0.0001355935,0.0001470092,0.00005138286,0.00000157839],"category_scores_gemma":[0.004979323,0.0001048552,0.00001939901,0.0002620184,0.0002431403,0.001205884,0.0004586917,0.0002166149,6.828743e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001673678,"about_ca_system_score_gemma":0.000007073892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009792835,"about_ca_topic_score_gemma":0.00008119734,"domain_scores_codex":[0.9988213,0.00004274927,0.0003665045,0.0002671218,0.0002315536,0.0002708181],"domain_scores_gemma":[0.9958491,0.000322088,0.003482681,0.0001932288,0.0001472896,0.00000557841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002534124,0.00003234762,0.8174187,0.0002585237,0.000009289765,6.225113e-7,0.001535893,0.0001953266,0.001702492,0.0009856692,0.00002209494,0.1778137],"study_design_scores_gemma":[0.0003430209,0.00001122124,0.9542206,0.0002197804,0.00002182323,0.000001506137,0.001370875,0.04258845,0.0001137591,0.00008722676,0.0009122784,0.0001094804],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963723,0.0006091003,0.002242366,0.0001269346,0.0001132201,0.0002884876,0.000002074999,0.00001681942,0.0002286982],"genre_scores_gemma":[0.9993971,0.0001243632,0.0001816905,0.00007800655,0.0001568706,0.00001974022,0.000002549638,0.00001471209,0.00002496438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1777042,"threshold_uncertainty_score":0.5961075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471383526545865,"score_gpt":0.2051285226352757,"score_spread":0.190414687369817,"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."}}