{"id":"W2593955014","doi":"10.1287/mnsc.2016.2635","title":"Full-Stock-Payment Marginalization in Merger and Acquisition Transactions","year":2017,"lang":"en","type":"article","venue":"Management Science","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"California Institute of Technology","keywords":"Pooling; Counterfactual thinking; Goodwill; Payment; Stock (firearms); Business; Monetary economics; Shares outstanding; Incentive; Accounting; Economics; Actuarial science; Finance; Microeconomics; Shareholder; Corporate governance","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":[0.001799812,0.0001207675,0.0002684043,0.0007631017,0.0004028556,0.001632215,0.0003744767,0.0003547354,0.005777624],"category_scores_gemma":[0.01432231,0.0001666682,0.0003473928,0.0009794314,0.0007782762,0.001373204,0.001031981,0.0007166195,0.0004483776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008176573,"about_ca_system_score_gemma":0.0008491029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01407456,"about_ca_topic_score_gemma":0.02128023,"domain_scores_codex":[0.9984128,0.0004186591,0.0001694293,0.0003303047,0.0003192645,0.0003495247],"domain_scores_gemma":[0.9837688,0.005589482,0.006826113,0.001015553,0.001232051,0.001567998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004098272,0.0001184211,0.9814917,0.00002066312,0.00005094043,0.0001704597,0.0008849504,0.0004335968,0.0009414082,0.003129094,0.0003605078,0.01198849],"study_design_scores_gemma":[0.000002212574,0.00003655098,0.997593,0.000003959303,0.000007591584,0.00006954205,0.0004532269,0.0008913488,0.000137575,0.0004953293,0.0003048424,0.000004880412],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979,0.000136,0.000198966,0.00008518624,0.000002292703,0.00000650102,0.0001544101,0.000004359416,0.001512242],"genre_scores_gemma":[0.9993371,0.00002323551,0.00004773364,0.000007108035,0.000004113827,0.00000194471,0.0001233849,0.000001055463,0.0004542809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01407456,"threshold_uncertainty_score":0.02798527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0167101703032763,"score_gpt":0.2338715197199,"score_spread":0.2171613494166237,"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."}}