{"id":"W2898146101","doi":"10.17722/ijme.v11i3.493","title":"Cost Efficiency of Thrift Banks in the Philippines: A Data Envelopment Approach","year":2018,"lang":"en","type":"article","venue":"International Journal of Management Excellence","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data envelopment analysis; Business; Econometrics; Economics; Industrial organization; Mathematics; Mathematical optimization","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":[0.003119694,0.0005350026,0.0007948349,0.003643505,0.0003551651,0.002088305,0.0006019174,0.0004856513,0.001807858],"category_scores_gemma":[0.009497504,0.0003339034,0.001125273,0.005576907,0.0004607537,0.001385025,0.0009199678,0.0006986773,0.0001917112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002894418,"about_ca_system_score_gemma":0.00163639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02365767,"about_ca_topic_score_gemma":0.011241,"domain_scores_codex":[0.9980831,0.0008570554,0.0001647533,0.0001970079,0.0005102556,0.000187758],"domain_scores_gemma":[0.9941311,0.003767913,0.0008043098,0.0003573385,0.0008601214,0.00007907797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001851138,0.0002177906,0.1592168,0.0004091955,0.0004373763,0.0004989079,0.0008124196,0.7764646,0.001056409,0.00959,0.0009687191,0.05014274],"study_design_scores_gemma":[0.00001296676,0.0001948504,0.1130699,0.0001249626,0.00009684524,0.0001337991,0.002153334,0.8743952,0.001479384,0.005470259,0.002807493,0.00006109502],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9541811,0.0005528076,0.03822944,0.0002426844,0.000008355992,0.0001535599,0.001861445,0.00005982044,0.004710893],"genre_scores_gemma":[0.9912288,0.0002823809,0.006899891,0.00001312525,0.000004108532,0.00008582452,0.0008629492,0.000008518282,0.0006143256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02365767,"threshold_uncertainty_score":0.04703993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09691442657901081,"score_gpt":0.2936631314074625,"score_spread":0.1967487048284517,"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."}}