{"id":"W3183082635","doi":"10.1007/s10479-021-04114-z","title":"Credit risk classification: an integrated predictive accuracy algorithm using artificial and deep neural networks","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Undersampling; Computer science; Oversampling; Machine learning; Artificial intelligence; Support vector machine; Artificial neural network; Resampling; Algorithm; Statistical classification; Data mining","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":[0.0008142991,0.0001180626,0.0001638265,0.0002469349,0.0008360209,0.0006601992,0.0001557997,0.0001080838,0.0001596121],"category_scores_gemma":[0.00090096,0.0001123567,0.00004722109,0.001084027,0.0002051665,0.001843718,0.0001448368,0.0003823804,0.000007209168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001592791,"about_ca_system_score_gemma":0.00008758242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001923493,"about_ca_topic_score_gemma":0.0009157711,"domain_scores_codex":[0.9984691,0.0001337838,0.0003453535,0.0003464328,0.0004039113,0.0003013922],"domain_scores_gemma":[0.9969287,0.00008206097,0.00007422821,0.000268297,0.002616326,0.00003042576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002242506,0.0009015417,0.006995792,0.00008488746,0.000109214,0.00004038819,0.0002914745,0.1249395,0.002823588,0.03959581,0.001893274,0.8221003],"study_design_scores_gemma":[0.0001243494,0.00004326526,0.03327008,0.00002672583,0.00002027686,0.000002422606,0.001123293,0.962969,0.0002438659,0.0007401445,0.001335227,0.0001013583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8630862,0.0006465393,0.1330578,0.001447226,0.0003847327,0.0004128464,0.00010057,0.00006905828,0.0007950977],"genre_scores_gemma":[0.996613,0.0002675652,0.0009824979,0.0001164774,0.001513729,0.00003233267,0.0004285355,0.00001698726,0.00002887003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8380295,"threshold_uncertainty_score":0.6430082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1978456949107665,"score_gpt":0.4008726326045339,"score_spread":0.2030269376937674,"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."}}