{"id":"W1526357621","doi":"10.2139/ssrn.2176977","title":"Debt Valuation Adjustments and Executive Compensation","year":2012,"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":"Wilfrid Laurier University; University of Waterloo","funders":"","keywords":"Executive compensation; Executive summary; Valuation (finance); Debt; Economics; Business; Accounting; Actuarial science; Finance; Corporate governance","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":[0.00109047,0.0002624239,0.0002431577,0.0007158571,0.0003868289,0.002558917,0.0003869092,0.001006982,0.009539546],"category_scores_gemma":[0.02141024,0.0001774872,0.0002612446,0.001003111,0.0004503186,0.001931205,0.0005273776,0.001404057,0.0008956553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007589206,"about_ca_system_score_gemma":0.0003799026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002493808,"about_ca_topic_score_gemma":0.00316036,"domain_scores_codex":[0.9996612,0.00009699355,0.00004777735,0.00005692443,0.00006273606,0.00007438775],"domain_scores_gemma":[0.9917161,0.003415648,0.003364417,0.0003901026,0.0005895502,0.0005241284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003481617,0.00128794,0.7273565,0.0001920777,0.0002414472,0.002152813,0.002435252,0.01523026,0.005183506,0.09451915,0.006931032,0.1409883],"study_design_scores_gemma":[0.00006709991,0.0002984852,0.9061278,0.00005195801,0.00007695861,0.0006629665,0.001684916,0.01189527,0.0008828201,0.06955896,0.008653911,0.00003901468],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9780427,0.001501127,0.001032527,0.001166153,0.00007164525,0.00001379547,0.0002636591,0.00002577933,0.01788262],"genre_scores_gemma":[0.9945828,0.0002618078,0.0001094186,0.00004788069,0.00004707566,0.000003202314,0.0001673701,0.000006008348,0.004774313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009539546,"threshold_uncertainty_score":0.03191298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03964975112241723,"score_gpt":0.3012449894633455,"score_spread":0.2615952383409283,"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."}}