{"id":"W3125436595","doi":"","title":"Information Overload and Disclosure Smoothing","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Smoothing; Volatility (finance); Stock price; Business; Market liquidity; Stock (firearms); Information overload; Set (abstract data type); Event study; Actuarial science; Accounting; Econometrics; Economics; Computer science; Finance; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006446236,0.0003266098,0.0004380468,0.001598431,0.0006979722,0.00203236,0.0005274061,0.0007700994,0.003191617],"category_scores_gemma":[0.06993133,0.0002598272,0.0004046973,0.0009549178,0.0008579317,0.002540612,0.001363179,0.001046257,0.0003640519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007899529,"about_ca_system_score_gemma":0.001030896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008286419,"about_ca_topic_score_gemma":0.00094609,"domain_scores_codex":[0.9956955,0.001516189,0.000526294,0.0004353749,0.001383072,0.0004435912],"domain_scores_gemma":[0.847216,0.07957575,0.05568088,0.009527503,0.004598525,0.003401272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001727456,0.001311722,0.4845664,0.0008826788,0.0006112283,0.0007476071,0.01026826,0.01105557,0.01731768,0.02474974,0.003380606,0.443381],"study_design_scores_gemma":[0.0002290226,0.002686951,0.8309987,0.0007167506,0.0006926676,0.002266809,0.00641209,0.02815923,0.01314796,0.08659527,0.0278178,0.0002766468],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9660171,0.002926806,0.01484362,0.002070279,0.00007427901,0.00008560917,0.0001322271,0.000144809,0.01370536],"genre_scores_gemma":[0.9964631,0.0003925004,0.002059047,0.0001877093,0.000140518,0.00001374291,0.00003917485,0.000008677518,0.00069556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006446236,"threshold_uncertainty_score":0.03409141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002589874290718009,"score_gpt":0.1772703431597221,"score_spread":0.1746804688690042,"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."}}