{"id":"W3198539970","doi":"10.1007/978-3-030-63591-6_64","title":"Calibration and Analysis of Structural Credit Risk Models with Occupation Time","year":2021,"lang":"en","type":"book-chapter","venue":"Springer proceedings in mathematics & statistics","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Credit default swap; Credit valuation adjustment; Credit risk; Bankruptcy; Asset (computer security); Econometrics; Credit event; Credit default swap index; Credit derivative; iTraxx; Economics; Actuarial science; Business; Finance; Computer science; Credit reference","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":[0.004466037,0.001029138,0.002041432,0.001369073,0.0007470182,0.002349567,0.003028142,0.002656563,0.00722066],"category_scores_gemma":[0.02382475,0.001177264,0.001655656,0.00159454,0.002193725,0.002887281,0.002311529,0.003088471,0.0009424167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001859638,"about_ca_system_score_gemma":0.002451471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01506733,"about_ca_topic_score_gemma":0.008161493,"domain_scores_codex":[0.9988255,0.0006297394,0.0000506364,0.0001910972,0.0001323441,0.0001708284],"domain_scores_gemma":[0.9852406,0.01153514,0.001157838,0.0009645417,0.0006871357,0.0004147281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004306311,0.00005649116,0.001852359,0.00003447543,0.00004290267,0.0000459923,0.00007595666,0.9055719,0.0001751846,0.0839228,0.001193401,0.006985371],"study_design_scores_gemma":[0.00001149505,0.000008445583,0.0002737286,0.000006853702,0.000007033369,0.000008761455,0.00001387579,0.9579731,0.00005403655,0.04141923,0.0002151498,0.000008353146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1669735,0.000951864,0.8200377,0.002269262,0.0001528407,0.00009445075,0.0008148284,0.0006459673,0.008059655],"genre_scores_gemma":[0.9471999,0.0007822347,0.04074777,0.0001786498,0.0001748472,0.0001842104,0.001056855,0.0002350149,0.009440435],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01506733,"threshold_uncertainty_score":0.02995926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01986898496531971,"score_gpt":0.2164356430959408,"score_spread":0.1965666581306211,"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."}}