{"id":"W2947807207","doi":"10.1111/1911-3846.12477","title":"Asymmetric Learning from Prices and Post‐Earnings‐Announcement Drift","year":2019,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Economics; Post-earnings-announcement drift; Private information retrieval; Arbitrage; Accrual; Asset (computer security); Financial economics; Value (mathematics); Monetary economics; Econometrics; Earnings response coefficient; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004342586,0.0002720612,0.0006726261,0.000701014,0.0002629978,0.001415958,0.0004585069,0.001018393,0.002800141],"category_scores_gemma":[0.04966216,0.000381343,0.0003313326,0.0005398045,0.001223283,0.001913088,0.001033872,0.001348309,0.0002943728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008316847,"about_ca_system_score_gemma":0.0003647046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001369879,"about_ca_topic_score_gemma":0.0007330764,"domain_scores_codex":[0.9988247,0.0003980561,0.00009966522,0.0002089847,0.000286933,0.000181653],"domain_scores_gemma":[0.9568655,0.02730875,0.01164302,0.002171048,0.001219109,0.0007923971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001998363,0.001255817,0.4735994,0.0002227543,0.0003903492,0.00129703,0.0009141894,0.2712479,0.01657056,0.1243979,0.003473474,0.1046323],"study_design_scores_gemma":[0.0001138916,0.0002498387,0.2652029,0.00003047539,0.00007612221,0.0003233388,0.0002171971,0.5623735,0.003161006,0.1673625,0.0007978282,0.00009134073],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803114,0.0001645857,0.01422949,0.0007790993,0.00002282593,0.00002307364,0.0001250465,0.00007569878,0.004268878],"genre_scores_gemma":[0.9993399,0.00003941122,0.0002665567,0.00002908893,0.000016299,0.000004056201,0.00002708921,0.000002988007,0.0002745726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004342586,"threshold_uncertainty_score":0.02296609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02878395103687453,"score_gpt":0.2686819402119415,"score_spread":0.239897989175067,"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."}}