{"id":"W2890050651","doi":"10.5430/ijba.v9n5p96","title":"Historical Trends and Transitions in Credit Risk Management of Chinese Commercial Banks","year":2018,"lang":"en","type":"article","venue":"International Journal of Business Administration","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Business; Risk management; Credit risk; Context (archaeology); Credit history; Commercial bank; Credit reference; Finance; Financial system; Political science","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":[0.001734918,0.0002220563,0.0002066669,0.003720125,0.001486816,0.001839439,0.0005804327,0.000571809,0.001421148],"category_scores_gemma":[0.00408407,0.0002119326,0.0001930695,0.006449364,0.001784613,0.002092802,0.001152188,0.0009320799,0.00009304685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008051847,"about_ca_system_score_gemma":0.004345523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07799972,"about_ca_topic_score_gemma":0.07255743,"domain_scores_codex":[0.998931,0.0001300892,0.0001533498,0.0002460616,0.0002942148,0.0002452581],"domain_scores_gemma":[0.9965817,0.0005739916,0.001072797,0.0001424855,0.001128482,0.0005004858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003139643,0.000121003,0.6285268,0.0007609014,0.0001184902,0.001320078,0.04089374,0.003628303,0.002357597,0.08024711,0.007170433,0.2345415],"study_design_scores_gemma":[0.000007614308,0.00008451642,0.9467387,0.0001940245,0.00004064965,0.0004856029,0.008167485,0.00270931,0.001320357,0.00369298,0.03648722,0.00007164837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9678345,0.01193856,0.0009458559,0.00435534,0.00005513518,0.00003895077,0.0004450945,0.0000235372,0.01436302],"genre_scores_gemma":[0.9925645,0.005356061,0.0003317274,0.0001645175,0.00004436508,0.0000138931,0.0001625623,0.000003890118,0.001358599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07799972,"threshold_uncertainty_score":0.1550914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02130539728488482,"score_gpt":0.2674242592415893,"score_spread":0.2461188619567045,"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."}}