{"id":"W6921035460","doi":"10.6084/m9.figshare.22579855.v1","title":"Mergers, Acquisitions and Stock Returns: The Informativeness of CEO Textual Tone","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stock (firearms); Phenomenon; Mergers and acquisitions; Logistic regression; Tone (literature); Stock price","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002785773,0.0002528749,0.0001504144,0.001952306,0.0003125988,0.002085309,0.0003268216,0.0004088117,0.004213523],"category_scores_gemma":[0.02924936,0.0001199482,0.000264417,0.001422589,0.0006383987,0.001165057,0.0009612376,0.0005223231,0.0007280938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003012366,"about_ca_system_score_gemma":0.000335052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002611821,"about_ca_topic_score_gemma":0.005069836,"domain_scores_codex":[0.9988506,0.0006409249,0.0000834328,0.0001188354,0.0002409978,0.00006516749],"domain_scores_gemma":[0.9634145,0.03082027,0.003547328,0.0009273786,0.001033178,0.0002573551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005144637,0.0002489469,0.7469947,0.0005060956,0.000154649,0.0006438511,0.009210572,0.003346942,0.01718208,0.005087255,0.002851751,0.2132587],"study_design_scores_gemma":[0.00001086265,0.0001902166,0.9567465,0.0001861937,0.0001142455,0.0004456501,0.003471599,0.02084573,0.005666029,0.004140337,0.008122097,0.00006055661],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9728481,0.0008095952,0.01207748,0.001431693,0.00004434902,0.00005291623,0.002205368,0.0001013054,0.01042934],"genre_scores_gemma":[0.9931521,0.0002764336,0.004559961,0.0000677161,0.00009126025,0.00003008875,0.0008792107,0.00002104411,0.0009220184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004213523,"threshold_uncertainty_score":0.01473272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02368227127856783,"score_gpt":0.2492404443946677,"score_spread":0.2255581731160998,"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."}}