{"id":"W2124737928","doi":"10.1145/1723112.1723130","title":"Acceleration of an analytical approach to collateralized debt obligation pricing","year":2010,"lang":"en","type":"article","venue":"","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Collateralized debt obligation; Speedup; Computer science; Convolution (computer science); Debt; Software; Dependability; Parallel computing; Collateral; Finance; Operating system; Software engineering; Business; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002708152,0.00007000182,0.0002005367,0.0002190531,0.00006906487,0.00005304747,0.0001024545,0.00008647986,0.0001518574],"category_scores_gemma":[0.0001036537,0.00007543702,0.00004722404,0.0003746558,0.00002269615,0.0002515305,0.00001918514,0.00007525816,0.00005152687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002017503,"about_ca_system_score_gemma":0.00001609102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003304964,"about_ca_topic_score_gemma":0.000150465,"domain_scores_codex":[0.9992025,0.000004439607,0.0004204478,0.000217222,0.00003257249,0.0001228538],"domain_scores_gemma":[0.9995112,0.00001559861,0.0001164419,0.0002213978,0.00005467126,0.00008072597],"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":[0.0000133433,0.0001119591,0.04260835,0.000005207601,0.000006273602,8.271789e-8,0.0003588386,0.0005404106,0.001233629,0.9530487,0.0001669378,0.00190625],"study_design_scores_gemma":[0.0004397425,0.0000762764,0.7836537,0.000002522986,0.000005619017,0.000001883701,0.00004463357,0.1875282,0.001540846,0.02099052,0.005518436,0.0001976244],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8965918,0.000005049184,0.05115027,0.0001522057,0.0001834236,0.0001944926,0.00001711842,0.00002404306,0.05168161],"genre_scores_gemma":[0.9776399,0.000002042216,0.02157865,0.00002902603,0.0001202464,0.00001361753,0.0000412747,0.000008912999,0.0005663399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9320582,"threshold_uncertainty_score":0.3076232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04242568170504854,"score_gpt":0.2623926649704598,"score_spread":0.2199669832654112,"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."}}