{"id":"W3134395777","doi":"10.3390/jrfm14030110","title":"Determinants of Differentiation of Cost of Risk (CoR) among Polish Banks during COVID-19 Pandemic","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Sample (material); Pandemic; Order (exchange); Variable (mathematics); Explanatory power; Credit risk; Econometrics; Demographic economics; Regression analysis; Economics; Capital (architecture); Business; Actuarial science; Geography; Statistics; Mathematics; Finance; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009431618,0.0001473732,0.0007434688,0.0004896853,0.00008320102,0.00001927957,0.0001874896,0.0001114401,0.00005287103],"category_scores_gemma":[0.001577109,0.0001577431,0.0002113258,0.0003157676,0.00009315203,0.0002145871,0.0001466491,0.0002223649,0.000001339423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000161773,"about_ca_system_score_gemma":0.00007702393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006468198,"about_ca_topic_score_gemma":0.0003062212,"domain_scores_codex":[0.9979841,0.00005297468,0.001418181,0.0002100882,0.0001171039,0.0002175274],"domain_scores_gemma":[0.9963832,0.0001775254,0.002959517,0.0002366919,0.000109889,0.0001332083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000136239,0.0001220574,0.9830645,0.0004035486,0.00005115545,0.00002226256,0.001052877,0.0003820705,0.00005194008,0.001048252,0.00005180704,0.01361326],"study_design_scores_gemma":[0.002093177,0.00008497705,0.9894019,0.0001378828,0.000107403,0.00001075507,0.0001778239,0.0002264229,0.0005180848,0.005967362,0.001136814,0.0001373837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841383,0.001526495,0.0134337,0.0000145738,0.000347031,0.0001560305,0.0002528803,0.000004115111,0.0001269367],"genre_scores_gemma":[0.9874578,0.01208021,0.0002726133,0.00004090562,0.00008450977,0.000002288958,0.000002751211,0.00001284368,0.0000460921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01347588,"threshold_uncertainty_score":0.6432576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02805861084987502,"score_gpt":0.2558316840931073,"score_spread":0.2277730732432323,"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."}}