{"id":"W4399033690","doi":"10.1002/mde.4271","title":"COVID‐19 and credit risk variation across banks: International insights","year":2024,"lang":"en","type":"article","venue":"Managerial and Decision Economics","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Credit risk; Business; China; Financial system; Variation (astronomy); Quarter (Canadian coin); Pandemic; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Economics; Actuarial science; Geography; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002253719,0.0001691817,0.0003805908,0.001843669,0.0003567724,0.002076908,0.000294327,0.0003945864,0.002410435],"category_scores_gemma":[0.007985618,0.0001126199,0.0003284543,0.00408435,0.0009071546,0.001443541,0.001603443,0.0009845692,0.0002167415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006952616,"about_ca_system_score_gemma":0.0004632397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01359848,"about_ca_topic_score_gemma":0.01046257,"domain_scores_codex":[0.9992,0.000237728,0.00007034876,0.000175413,0.0001555371,0.0001609058],"domain_scores_gemma":[0.9900411,0.002999818,0.004722829,0.0006512679,0.0009975571,0.000587617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005932387,0.00003118172,0.9791709,0.00002297766,0.0001066441,0.0001428072,0.0005214378,0.002540381,0.0002155268,0.004717737,0.00105563,0.01141545],"study_design_scores_gemma":[0.000004580706,0.00004708454,0.9880726,0.00004880564,0.0000337904,0.0001252978,0.001558434,0.003697279,0.0002483512,0.002717773,0.003424464,0.00002152561],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852942,0.001262614,0.0012318,0.001259003,0.0000224508,0.00001318662,0.001290438,0.00001288376,0.009613345],"genre_scores_gemma":[0.9989462,0.0002037255,0.00008838472,0.00004285185,0.00001351817,0.000002755857,0.0004245245,0.00000235004,0.0002756672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01359848,"threshold_uncertainty_score":0.02703863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03192786393305558,"score_gpt":0.2790722277555486,"score_spread":0.2471443638224931,"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."}}