{"id":"W3206021300","doi":"10.3390/jrfm14100485","title":"Self-Organising (Kohonen) Maps for the Vietnam Banking Industry","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Self-organizing map; Banking industry; Vietnamese; Lerner index; Stock market; Retail banking; Business; Economics; Market power; Industrial organization; Financial system; Artificial neural network; Microeconomics; Artificial intelligence; Computer 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":[0.0005208344,0.0002426661,0.0001852381,0.001371983,0.0003322395,0.0007361184,0.0003921775,0.0004457817,0.001525758],"category_scores_gemma":[0.002263051,0.0001610109,0.0005023539,0.0008066641,0.0003203227,0.0008377383,0.0003667061,0.0003517862,0.0002382417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004903175,"about_ca_system_score_gemma":0.0005084724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0116569,"about_ca_topic_score_gemma":0.009926577,"domain_scores_codex":[0.9998747,0.00003874748,0.000008253182,0.00003052748,0.00003091278,0.00001689434],"domain_scores_gemma":[0.9991159,0.0006033822,0.0000767334,0.00005060298,0.000126084,0.00002731277],"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":[0.0001638426,0.0001358815,0.03233695,0.0003883651,0.0001663566,0.0004258384,0.001417615,0.6515067,0.004303283,0.0256475,0.00255759,0.28095],"study_design_scores_gemma":[0.000002650542,0.00001583988,0.003951346,0.00001247624,0.000004989946,0.00004642644,0.0001414254,0.9860023,0.0002960698,0.008809115,0.0007080858,0.000009223842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4522333,0.001326402,0.5352684,0.0005036979,0.0001003596,0.000172839,0.0004727032,0.0006773088,0.009245001],"genre_scores_gemma":[0.9153719,0.0002412573,0.08249465,0.00003466641,0.00001800548,0.00005366238,0.0001868869,0.00002518631,0.001573874],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0116569,"threshold_uncertainty_score":0.0231781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01255665535182363,"score_gpt":0.2115298506082892,"score_spread":0.1989731952564655,"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."}}