{"id":"W2185613623","doi":"","title":"Fast CDO Computations in the Affine Markov Chain Model","year":2005,"lang":"en","type":"article","venue":"","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Collateralized debt obligation; Affine transformation; Computation; Markov chain; Computer science; Hazard; Algorithm; Markov chain Monte Carlo; Mathematical optimization; Mathematics; Economics; Finance; Artificial intelligence; Collateral; Machine learning","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":[0.001473979,0.0005229012,0.000947141,0.0006232226,0.0008022995,0.001170987,0.0009755758,0.0009130338,0.01069231],"category_scores_gemma":[0.008287815,0.0004750023,0.0006034496,0.000928694,0.0008428817,0.001790025,0.001254514,0.001764182,0.0009158428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001480693,"about_ca_system_score_gemma":0.001935118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02119196,"about_ca_topic_score_gemma":0.01711854,"domain_scores_codex":[0.9995317,0.0001429467,0.00002830464,0.00008717005,0.0001232314,0.00008662938],"domain_scores_gemma":[0.9951453,0.003660147,0.0002550804,0.0004172597,0.0003458015,0.0001764558],"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":[0.0000927131,0.00004097564,0.00178461,0.00003749007,0.00001995325,0.0001362241,0.00006341584,0.9252304,0.0005802086,0.05390078,0.0009902837,0.017123],"study_design_scores_gemma":[0.000004881358,0.000002695919,0.00007255933,0.000002602718,0.000001603463,0.000006623273,0.000005850299,0.9898336,0.0001305198,0.009772339,0.0001644313,0.000002404372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08556092,0.0002061603,0.9056005,0.0005360786,0.00006570443,0.00006316348,0.0003437638,0.001060325,0.006563529],"genre_scores_gemma":[0.8177097,0.0001971455,0.1761821,0.0001382935,0.00005765476,0.0001238755,0.0004589657,0.0001993679,0.004932892],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02119196,"threshold_uncertainty_score":0.04213721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02817278395415169,"score_gpt":0.2267841792705715,"score_spread":0.1986113953164198,"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."}}