{"id":"W1544325966","doi":"10.1023/a:1021822103696","title":"Measuring Inefficiency Via Potential Improvements","year":2003,"lang":"en","type":"article","venue":"Journal of Productivity Analysis","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":79,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Inefficiency; Benchmark (surveying); Data envelopment analysis; Selection (genetic algorithm); Econometrics; Computer science; Index (typography); Economics; Mathematical optimization; Mathematics; Microeconomics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02173528,0.0002460399,0.001049964,0.003273415,0.0003623452,0.0003680973,0.001174937,0.00008818504,0.0004763349],"category_scores_gemma":[0.01321079,0.0001778435,0.001408271,0.0109462,0.0001751339,0.001073159,0.00009879102,0.0004403246,0.00007077856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001534946,"about_ca_system_score_gemma":0.0002391823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003899582,"about_ca_topic_score_gemma":0.00005468942,"domain_scores_codex":[0.9914289,0.001135484,0.001948992,0.0007066177,0.004342228,0.0004377908],"domain_scores_gemma":[0.9935893,0.0003443066,0.002304601,0.00111446,0.002428324,0.0002189711],"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":[0.0001518304,0.003207236,0.1635035,0.00001651426,0.006181831,0.0001964729,0.001268453,0.6214032,0.1414153,0.0007565711,0.0008873689,0.06101175],"study_design_scores_gemma":[0.005890599,0.002471568,0.3792933,0.0001138548,0.04180467,0.001292188,0.004793617,0.1905871,0.2353022,0.1114241,0.02273967,0.004287067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6563402,0.0003084552,0.3415487,0.0005780653,0.0005329062,0.00006401081,0.000001572799,0.00001000507,0.0006160127],"genre_scores_gemma":[0.9954422,0.000008706639,0.003561968,0.00005017447,0.0002221008,9.330255e-7,4.488466e-7,0.00001149138,0.0007019811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.430816,"threshold_uncertainty_score":0.9951013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07024273685987614,"score_gpt":0.3345905253088883,"score_spread":0.2643477884490122,"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."}}