{"id":"W1924806893","doi":"","title":"Непараметрические оценки эффективности российских банков","year":2010,"lang":"ru","type":"preprint","venue":"Munich Personal RePEc Archive (Munich University)","topic":"Economic and Technological Developments in Russia","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Econometrics; Quarter (Canadian coin); Economics; Parametric statistics; Spearman's rank correlation coefficient; Statistics; Mathematics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002021165,0.0003492341,0.0006447782,0.002580168,0.0007345098,0.002265916,0.0003761336,0.0003503218,0.01802771],"category_scores_gemma":[0.004056065,0.0002560611,0.0007266256,0.002768636,0.000752815,0.0007195135,0.000671076,0.0009925729,0.005972965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009142843,"about_ca_system_score_gemma":0.0008269925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003118896,"about_ca_topic_score_gemma":0.00210926,"domain_scores_codex":[0.9986516,0.000228592,0.000120702,0.0002496327,0.0006234111,0.000126083],"domain_scores_gemma":[0.9983252,0.0007166744,0.0003809463,0.0002835405,0.0002446994,0.00004898597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005267995,0.0001516497,0.04350077,0.0007256545,0.0002330378,0.0006288643,0.005646,0.01088594,0.00725688,0.2785844,0.03324598,0.618614],"study_design_scores_gemma":[0.00006296882,0.0004499029,0.3017367,0.0003400437,0.0001925683,0.001927342,0.003383068,0.01473307,0.01121795,0.102157,0.5635905,0.000208928],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.534777,0.01192932,0.1242012,0.002906132,0.001134887,0.0003266285,0.01920238,0.0009794707,0.304543],"genre_scores_gemma":[0.8931451,0.004422324,0.04554767,0.00008490429,0.0003413153,0.0005881583,0.00558673,0.0002426683,0.05004116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01802771,"threshold_uncertainty_score":0.06030875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02385465846598579,"score_gpt":0.2423316510810574,"score_spread":0.2184769926150717,"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."}}