{"id":"W2981848207","doi":"10.2139/ssrn.3437865","title":"The Anatomy of Acquirer Returns","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Economics; Econometrics; Composition (language); Component (thermodynamics); Monetary economics; Financial economics","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":[0.0008042955,0.0001783539,0.0001715038,0.00154342,0.0007946369,0.00488987,0.0004859746,0.001305722,0.01571292],"category_scores_gemma":[0.005223737,0.0002569378,0.0001990462,0.001254031,0.00529359,0.007228574,0.00113652,0.001853217,0.003407179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001304729,"about_ca_system_score_gemma":0.0009119692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002210035,"about_ca_topic_score_gemma":0.002308273,"domain_scores_codex":[0.9993668,0.0002435854,0.00002487739,0.00009964772,0.0001852992,0.00007980147],"domain_scores_gemma":[0.9986034,0.0007554242,0.000107327,0.0002101005,0.000218862,0.0001047488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000007804091,0.000004824685,0.0006332021,0.000009261616,0.000001822284,0.00008825506,0.0005106121,0.0001545876,0.0003439102,0.9818767,0.001937597,0.01443141],"study_design_scores_gemma":[0.000005814158,0.00002180072,0.005795266,0.00005124172,0.000004314321,0.0005704072,0.0005817942,0.001442542,0.0003452493,0.9325555,0.05860941,0.00001667193],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08161091,0.006676581,0.08070445,0.02061793,0.0003064104,0.00004173637,0.0003792834,0.0004267477,0.809236],"genre_scores_gemma":[0.8456647,0.004541503,0.01701503,0.0009393845,0.0007126288,0.00004379913,0.0001347073,0.0002092603,0.130739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01571292,"threshold_uncertainty_score":0.05256492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005225253282456522,"score_gpt":0.2080822525341495,"score_spread":0.202856999251693,"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."}}