{"id":"W2974436995","doi":"10.2139/ssrn.3438049","title":"Whose Earnings and Profits? What Dividend? A Discussion Based on the Dr. Pepper - Keurig Transaction","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Reporting and Valuation Research","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Merck Canada Inc. (Canada)","funders":"","keywords":"Pepper; Earnings; Database transaction; Dividend; Business; Accounting; Earnings management; Economics; Finance; Database; Computer science","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":[0.01025497,0.0006985159,0.00127703,0.001666297,0.003450028,0.008447648,0.002134885,0.01914133,0.007542175],"category_scores_gemma":[0.02164184,0.0004496265,0.000604021,0.003361264,0.01535569,0.01896347,0.002839362,0.01689117,0.001685161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004020356,"about_ca_system_score_gemma":0.004252327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009457127,"about_ca_topic_score_gemma":0.008483073,"domain_scores_codex":[0.9964851,0.001823608,0.0001812414,0.0005120889,0.0007716489,0.0002262436],"domain_scores_gemma":[0.9850985,0.01300756,0.0003478758,0.0002141821,0.0009435809,0.0003883497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004767458,0.00002128145,0.0003279138,0.0001363382,0.00001231811,0.0002952902,0.001581384,0.0002191346,0.0001511185,0.7422988,0.2225762,0.03233255],"study_design_scores_gemma":[0.00003444831,0.00004526383,0.001278589,0.001129493,0.00001428242,0.0004136401,0.002428387,0.0008566639,0.0002344033,0.5997307,0.3937596,0.00007446733],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0009018499,0.04403776,0.001321809,0.9372566,0.003340194,0.000008940281,0.00003864885,0.000006470535,0.01308761],"genre_scores_gemma":[0.1121658,0.1589203,0.005110396,0.6473206,0.04142332,0.0001174869,0.00008573566,0.0001483594,0.03470806],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01914133,"threshold_uncertainty_score":0.05423409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01789937792950202,"score_gpt":0.2615503664227683,"score_spread":0.2436509884932663,"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."}}