{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001282057,0.0005507788,0.0004827575,0.002185547,0.0003574941,0.001800389,0.0004005003,0.001045482,0.002326733],"category_scores_gemma":[0.009837386,0.000199245,0.0004819848,0.002656197,0.0002117331,0.001854065,0.0006451332,0.001054479,0.001436898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004583179,"about_ca_system_score_gemma":0.000410866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01835886,"about_ca_topic_score_gemma":0.01350709,"domain_scores_codex":[0.9995903,0.0001626253,0.00002311983,0.00006315047,0.00008917652,0.00007169246],"domain_scores_gemma":[0.9906468,0.007148121,0.0007679163,0.0003145561,0.0008059148,0.0003166842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008937664,0.0005224523,0.8151312,0.0001131701,0.0002827686,0.0006062664,0.0005982062,0.06209467,0.00208651,0.001865629,0.01875996,0.09704538],"study_design_scores_gemma":[0.00004760756,0.0002309589,0.4956441,0.00004165458,0.0001951445,0.0003819965,0.0005778715,0.4913629,0.001668078,0.004159827,0.005637625,0.00005215639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874403,0.0009066036,0.002898757,0.0009958508,0.00007557216,0.00002253314,0.003827827,0.0001921786,0.003640321],"genre_scores_gemma":[0.9936302,0.0003684636,0.0008952325,0.00006519866,0.0001671563,0.00001400697,0.003846417,0.0000272176,0.000986055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01835886,"threshold_uncertainty_score":0.03650397,"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."}}