{"id":"W4297825325","doi":"10.1111/abac.12265","title":"The Post‐earnings Announcement Drift: A Pre‐earnings Announcement Effect? A Multi‐period Analysis","year":2022,"lang":"en","type":"article","venue":"Abacus","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Post-earnings-announcement drift; Inefficiency; Earnings; Economics; Earnings response coefficient; Financial economics; Econometrics; Order (exchange); Monetary economics; Accounting; Finance; Microeconomics","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002539206,0.0005960779,0.0006032994,0.0005098709,0.003372831,0.001056167,0.00136313,0.00006912617,0.001522726],"category_scores_gemma":[0.00314625,0.0004966179,0.0005060175,0.002944018,0.0001789152,0.0008665613,0.002269692,0.0008799324,0.0006402112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004032364,"about_ca_system_score_gemma":0.00005920096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002466965,"about_ca_topic_score_gemma":0.0003730545,"domain_scores_codex":[0.9950789,0.0001567117,0.0007450147,0.001079774,0.001791003,0.001148652],"domain_scores_gemma":[0.9892495,0.0001842762,0.009302254,0.0009165294,0.0002998796,0.00004753589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000962308,0.0008513191,0.7543603,0.0003948105,0.004647446,0.000381771,0.004909003,0.03514337,0.00285391,0.004532045,0.04761846,0.1433453],"study_design_scores_gemma":[0.001330253,0.0001817732,0.1617532,0.00002546196,0.0008777345,0.000004482523,0.001070175,0.007994913,0.00001617732,0.00002960591,0.8261008,0.0006154011],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9640623,0.000565356,0.01814223,0.005078146,0.00111768,0.00190805,0.00004242516,0.0006508154,0.008432943],"genre_scores_gemma":[0.9819587,0.00003633432,0.0001648828,0.002679657,0.0005776241,0.0008845293,0.0002859297,0.00009561463,0.01331673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7784823,"threshold_uncertainty_score":0.9999808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005489354014400587,"score_gpt":0.2109632046411134,"score_spread":0.2054738506267128,"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."}}