{"id":"W2471591028","doi":"10.21314/jcr.2007.058","title":"Affine Markov chain model of multifirm credit migration","year":2007,"lang":"en","type":"article","venue":"The Journal of Credit Risk","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Collateralized debt obligation; Affine transformation; Markov chain; Computer science; Credit derivative; Interest rate; Credit risk; Econometrics; Economics; Mathematics; Actuarial science; Finance; Machine learning; Collateral","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":[0.0037096,0.0001416817,0.0004273872,0.0003459343,0.0001468028,0.00002080943,0.000364334,0.000117597,0.00009917615],"category_scores_gemma":[0.0005850976,0.0001154622,0.0002301167,0.0002927673,0.0001228597,0.0002536153,0.00004033928,0.0003376008,0.00002243489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007996395,"about_ca_system_score_gemma":0.00005394204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003624855,"about_ca_topic_score_gemma":0.0003562436,"domain_scores_codex":[0.9981501,0.00002600484,0.001325998,0.0001192032,0.0001343624,0.0002443086],"domain_scores_gemma":[0.9972035,0.0002719496,0.00190926,0.0003148791,0.0002059799,0.00009445694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003702265,0.001692567,0.4049181,0.0001332396,0.0007768245,0.00002915432,0.01667931,0.1994447,0.007554543,0.1538717,0.09815778,0.1130398],"study_design_scores_gemma":[0.002608703,0.0006516906,0.6544178,0.00008368351,0.0001882326,0.00005663196,0.0005448193,0.2116783,0.003095192,0.0678342,0.05832193,0.0005189052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.820755,0.001314518,0.1734747,0.0005366619,0.001159924,0.0001221942,0.0001817031,0.000009015288,0.002446242],"genre_scores_gemma":[0.9922445,0.001634054,0.003768968,0.000012809,0.001516911,0.000001070074,0.00000557108,0.00002050322,0.0007955589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2494997,"threshold_uncertainty_score":0.4708412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02439822149079537,"score_gpt":0.2308269287890049,"score_spread":0.2064287072982096,"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."}}