{"id":"W2064846354","doi":"10.5430/afr.v3n4p31","title":"Influence of Auditor Office Size on Earnings Prediction","year":2014,"lang":"en","type":"article","venue":"Accounting and Finance Research","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Accrual; Audit; Earnings; Business; Reputation; Value (mathematics); Cash flow; Accounting; Predictive value; Econometrics; Economics; Statistics","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":[0.003129708,0.0001909996,0.000257913,0.0002894856,0.0005120318,0.0002407809,0.0004259941,0.0001031363,0.00003080504],"category_scores_gemma":[0.03279435,0.0001900751,0.00004591543,0.0009757332,0.0002650613,0.001052262,0.0004304719,0.0006273153,0.000326183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004003672,"about_ca_system_score_gemma":0.0000250199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007923076,"about_ca_topic_score_gemma":0.00001667462,"domain_scores_codex":[0.9974784,0.00004272463,0.0003615846,0.0005460109,0.0009733348,0.0005979852],"domain_scores_gemma":[0.9947684,0.0006672741,0.003571035,0.0003878849,0.0005934286,0.00001197878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003638323,0.0002688901,0.5906523,0.001531483,0.00005705668,0.00001285485,0.0003347415,0.01723194,0.005796986,0.06888294,0.02810896,0.2867579],"study_design_scores_gemma":[0.0003864319,0.00005603282,0.6225053,0.0003584645,0.000009488855,6.757448e-7,0.00005255389,0.003553377,0.000129449,0.0007995793,0.3719823,0.0001663033],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854552,0.00004180397,0.001140017,0.0005117981,0.0001500017,0.0002350704,0.000002518678,0.0001014349,0.01236218],"genre_scores_gemma":[0.9964271,0.0001168954,0.0001259242,0.0003953365,0.001480702,0.00003253968,0.00000406541,0.00003675025,0.001380716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3438734,"threshold_uncertainty_score":0.9753528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01238208714422726,"score_gpt":0.2537828714012554,"score_spread":0.2414007842570282,"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."}}