{"id":"W3082864482","doi":"","title":"ANALYSIS OF DIFFERENCES IN FINANCIAL PRODUCTIVITY BETWEEN GOVERNMENT BANKS AND PRIVATE BANKS USING VALUE ADDED METHOD","year":2020,"lang":"en","type":"article","venue":"","topic":"Financial Analysis and Corporate Governance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Adidas (Canada)","funders":"","keywords":"Mathematics; Business administration; Financial system; Physics; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003679488,0.0003199046,0.0003847862,0.003086936,0.0004339486,0.001338194,0.0005032017,0.0004603182,0.006605851],"category_scores_gemma":[0.01132826,0.0001344543,0.0005592704,0.00336716,0.0004404981,0.0007066163,0.0008180096,0.0006607632,0.001048754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006156684,"about_ca_system_score_gemma":0.0006284278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002686512,"about_ca_topic_score_gemma":0.002829247,"domain_scores_codex":[0.9959651,0.001561465,0.000496087,0.0005244031,0.001130863,0.0003220845],"domain_scores_gemma":[0.986895,0.008002868,0.001974723,0.0007805313,0.001951169,0.0003958321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006427174,0.0003974719,0.882845,0.0001537976,0.0002832333,0.0002145597,0.002756697,0.0007016848,0.001995617,0.001398957,0.001844912,0.1067652],"study_design_scores_gemma":[0.00002770474,0.0006173574,0.9764289,0.00008563948,0.0001050032,0.0002705487,0.006693102,0.006411128,0.003453258,0.001582281,0.004286198,0.00003894892],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815919,0.0002916159,0.008721017,0.0001955085,0.00008837658,0.000220324,0.001650155,0.00005827931,0.007182897],"genre_scores_gemma":[0.98848,0.0001080757,0.007119926,0.00003147402,0.00002672055,0.0002636876,0.0009144346,0.00001135114,0.00304424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006605851,"threshold_uncertainty_score":0.02209884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04020357330890378,"score_gpt":0.2329380180292964,"score_spread":0.1927344447203926,"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."}}