{"id":"W3124024278","doi":"","title":"Credit Enhancement and Loan Default Risk Premiums","year":2002,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Business; Loan; Default; Actuarial science; Credit risk; Leverage (statistics); Non-performing loan; Debt; Finance","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":[0.001432604,0.0002608961,0.0003646714,0.0006079461,0.000179195,0.00113197,0.0004024328,0.0006312928,0.003766237],"category_scores_gemma":[0.01203287,0.0001287051,0.0002979099,0.0004067458,0.000668994,0.001146654,0.0007016527,0.001063102,0.0002211175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005061318,"about_ca_system_score_gemma":0.0001989715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004884362,"about_ca_topic_score_gemma":0.0003388878,"domain_scores_codex":[0.9995745,0.0001133558,0.00002940447,0.00006436023,0.0001390404,0.00007934174],"domain_scores_gemma":[0.9925975,0.003627231,0.002097708,0.0007358837,0.0004372975,0.0005044364],"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":[0.001285266,0.0007071128,0.2041899,0.0002833104,0.0003433411,0.001227669,0.0009125681,0.2779206,0.03909511,0.2970893,0.003137407,0.1738085],"study_design_scores_gemma":[0.0001234766,0.0005323809,0.2702231,0.00008488163,0.000201694,0.001082177,0.0002962691,0.5119202,0.01188718,0.2002176,0.003341039,0.00009016416],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9657746,0.0007524288,0.02523893,0.0004887217,0.00001313554,0.00002699768,0.0001501208,0.0001090613,0.007446049],"genre_scores_gemma":[0.9990676,0.00006501433,0.0004852515,0.000006595467,0.00001158202,0.000002256736,0.0000197749,0.000002265063,0.0003398074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003766237,"threshold_uncertainty_score":0.01259935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01152019410295649,"score_gpt":0.1901610385161039,"score_spread":0.1786408444131474,"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."}}