{"id":"W4416918397","doi":"10.1016/j.jbankfin.2025.107598","title":"Predicting financial stability with TopicGPT: Insights from corporate and central bank communications","year":2025,"lang":"en","type":"article","venue":"Journal of Banking & Finance","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Narodowe Centrum Nauki","keywords":"Earnings; Systemic risk; Financial stability; Debt; Index (typography); Complement (music); Stability (learning theory); Key (lock); Central bank","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":[0.000149104,0.0001403994,0.0002691223,0.0001254403,0.0003314969,0.0001787145,0.0003149553,0.00007437592,0.00001572153],"category_scores_gemma":[0.0001450259,0.000115841,0.00005817786,0.000378353,0.0001359457,0.000934542,0.000154612,0.000316944,0.000001337455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005296618,"about_ca_system_score_gemma":0.0001157987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003838812,"about_ca_topic_score_gemma":0.0006217121,"domain_scores_codex":[0.9989802,0.00001871652,0.0004547271,0.000173227,0.0001905358,0.0001826167],"domain_scores_gemma":[0.9985357,0.00006751098,0.0008047056,0.0002932286,0.0002894554,0.000009400682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003633529,0.0002210871,0.8660745,0.0001646659,0.00005031327,0.00003015084,0.0003072307,0.0001493391,0.0008756164,0.1020841,0.0008788548,0.02880075],"study_design_scores_gemma":[0.00074318,0.00003297021,0.956302,0.0006581994,0.00008710063,0.000002671858,0.00006389318,0.002979795,0.000128535,0.02076162,0.01811364,0.000126323],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920236,0.001184862,0.002511037,0.0007384431,0.000569527,0.000114153,0.000008747557,0.00002617433,0.002823445],"genre_scores_gemma":[0.9979867,0.0001722946,0.000857998,0.0003721469,0.0005644533,0.000004116679,0.00001046411,0.000007946413,0.00002385675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09022757,"threshold_uncertainty_score":0.472386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01756746441095366,"score_gpt":0.2071729988182409,"score_spread":0.1896055344072872,"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."}}