{"id":"W4402919126","doi":"10.3390/jrfm17100432","title":"Financial Distress Prediction in the Nordics: Early Warnings from Machine Learning Models","year":2024,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Norges Forskningsråd","keywords":"Financial distress; Distress; Computer science; Psychology; Artificial intelligence; Machine learning; Business; Financial system; Clinical psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001748288,0.0007792936,0.0007521478,0.001569082,0.0003585019,0.001534608,0.0008162681,0.0009810405,0.000538466],"category_scores_gemma":[0.004568763,0.0003134849,0.0004713381,0.001177456,0.0003374913,0.0007380553,0.0008013883,0.001450898,0.0001953784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009692208,"about_ca_system_score_gemma":0.001059202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05166816,"about_ca_topic_score_gemma":0.043482,"domain_scores_codex":[0.9996195,0.0001623586,0.00002440131,0.00008213788,0.00005746695,0.00005418487],"domain_scores_gemma":[0.9984311,0.0008712449,0.0002270175,0.0001666547,0.000211876,0.00009212444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003163033,0.0002885764,0.1016729,0.00009043197,0.0001831713,0.000369597,0.0001003184,0.8341447,0.000423673,0.002400086,0.008751895,0.05125822],"study_design_scores_gemma":[0.00003435089,0.00004798703,0.01922323,0.00004713923,0.00003056592,0.00003677395,0.00007448845,0.9752762,0.0004178139,0.00342818,0.001364809,0.00001839203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9365276,0.002734954,0.04923453,0.00201858,0.0001559868,0.00006430051,0.005586755,0.0005045665,0.003172787],"genre_scores_gemma":[0.98388,0.0004177342,0.009974955,0.00009542931,0.00005814953,0.00002346963,0.004723188,0.00001385546,0.0008132149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05166816,"threshold_uncertainty_score":0.1027349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008341247382831407,"score_gpt":0.1845366729961596,"score_spread":0.1761954256133282,"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."}}