{"id":"W4391544092","doi":"10.5539/ijef.v16n3p64","title":"Constructing a Financial Risk Early Warning Model for Chinese Public Hospitals Based on Machine Learning","year":2024,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shanghai Municipal Education Commission; Shanghai Education Development Foundation","keywords":"Warning system; Financial risk; Finance; Early warning system; Business; Actuarial science; Computer science; Telecommunications","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":[0.0009332781,0.0001851771,0.0003924496,0.0004683021,0.0001334269,0.0003480661,0.0003016174,0.00008664713,0.00001077678],"category_scores_gemma":[0.0004899498,0.0001933438,0.0002499039,0.00009855047,0.00005514918,0.0005275601,0.00004938806,0.0003702027,0.00001563745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001678568,"about_ca_system_score_gemma":0.00008831202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004095247,"about_ca_topic_score_gemma":0.0000291008,"domain_scores_codex":[0.9985675,0.000009607059,0.0008317232,0.0003156866,0.00004398926,0.0002315564],"domain_scores_gemma":[0.9987766,0.0001512876,0.0008016987,0.0001010403,0.0001249836,0.00004442002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001536676,0.00004965809,0.08444116,0.0000233461,0.00009817391,0.00001935221,0.0003596298,0.1231339,6.0169e-7,0.7353492,0.0001131444,0.05625813],"study_design_scores_gemma":[0.000797876,0.0001958841,0.007454368,0.00007341877,0.000007451609,0.00001001354,0.00001216747,0.8861125,0.00000425971,0.07818678,0.02694375,0.0002015824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9227673,0.002414065,0.06876319,0.001511224,0.002148737,0.0001512529,0.0004838883,0.00001454185,0.001745759],"genre_scores_gemma":[0.9897224,0.004859439,0.004424145,0.0002048909,0.0005064724,0.00001464826,0.00001292456,0.00002982178,0.0002252678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7629786,"threshold_uncertainty_score":0.7884332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0157602210781464,"score_gpt":0.2241604633564961,"score_spread":0.2084002422783497,"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."}}