{"id":"W2935932094","doi":"10.3390/risks7020040","title":"Recent Regulation in Credit Risk Management: A Statistical Framework","year":2019,"lang":"en","type":"article","venue":"Risks","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Credit risk; Volatility (finance); Loan; Risk management; Business; Actuarial science; European union; Credit valuation adjustment; Economics; Stress test; Credit reference; Finance; International economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01740702,0.001210848,0.00149884,0.003183605,0.0009697145,0.005051613,0.002638908,0.003253976,0.0025169],"category_scores_gemma":[0.03647798,0.0008869492,0.001719444,0.003640948,0.007371573,0.005166385,0.002338936,0.005454588,0.0003709345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004236559,"about_ca_system_score_gemma":0.002184511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007156267,"about_ca_topic_score_gemma":0.003696822,"domain_scores_codex":[0.9922706,0.004139317,0.0004696355,0.001276756,0.001500694,0.00034299],"domain_scores_gemma":[0.9653627,0.02346336,0.004674171,0.002888239,0.003092749,0.0005187219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009343425,0.00003246015,0.001294227,0.00004215689,0.00003531866,0.00004359526,0.00005454279,0.06020433,0.00008666803,0.9265434,0.001487099,0.01016683],"study_design_scores_gemma":[0.00001104232,0.00003320038,0.001558121,0.00006364017,0.00002663938,0.00004364691,0.00002949132,0.2122548,0.0001326262,0.7798526,0.00595123,0.00004304725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02425127,0.01837554,0.9245962,0.01734909,0.0004148223,0.00005243143,0.0004821491,0.0001963287,0.01428221],"genre_scores_gemma":[0.8253,0.02389344,0.1311956,0.002781508,0.004938888,0.0003238991,0.0008509501,0.000187366,0.0105285],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01740702,"threshold_uncertainty_score":0.09205818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03415914382899445,"score_gpt":0.2661351976686107,"score_spread":0.2319760538396163,"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."}}