{"id":"W7089650737","doi":"10.4236/ti.2025.164011","title":"Artificial Intelligence and Capital Solvency Ratios: Theoretical Foundations, Empirical Evidence, and Systemic Implications","year":2025,"lang":"en","type":"article","venue":"Technology and Investment","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Solvency; Systemic risk; Corporate governance; Capital requirement; Empirical evidence; Capital market; Financial market; Economic capital","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":[0.0001409647,0.00009820111,0.0001187929,0.0002951724,0.0003086674,0.0001108991,0.00007323391,0.0001251381,0.00001689663],"category_scores_gemma":[0.0001784007,0.00008599615,0.0000133475,0.0003630434,0.0006212239,0.0003010788,0.0001610301,0.0001080698,0.000009060723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001747444,"about_ca_system_score_gemma":0.00002251373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002128843,"about_ca_topic_score_gemma":0.00002710502,"domain_scores_codex":[0.9993524,0.000007082416,0.0002183969,0.0002469665,0.00004872435,0.0001264178],"domain_scores_gemma":[0.9997095,0.00003972252,0.00005607526,0.0001325848,0.0000532078,0.00000894296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007482967,0.00003507882,0.02720685,0.00006730369,0.000008790809,6.641084e-7,0.00002621899,5.689133e-7,0.000174096,0.9556287,0.0002607878,0.01658349],"study_design_scores_gemma":[0.00004502456,0.0000265921,0.03795705,0.0001468224,0.00005726342,0.000007742156,0.0003858843,0.001546172,0.0001059279,0.9585429,0.001085445,0.00009314431],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9727229,0.00229466,0.008105136,0.01433015,0.0001303779,0.0003260348,0.000003449801,0.0001568735,0.001930424],"genre_scores_gemma":[0.9982666,0.0002154854,0.00015957,0.001168161,0.00006456518,0.00009145207,0.000009752841,0.000003729804,0.00002067747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02554371,"threshold_uncertainty_score":0.3506821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04044717175305981,"score_gpt":0.2885612648518921,"score_spread":0.2481140930988323,"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."}}