{"id":"W2169223506","doi":"","title":"Guide to the Measurement of Government Productivity","year":2002,"lang":"en","type":"article","venue":"International productivity monitor","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Productivity; Government (linguistics); Treasury; Economics; Index (typography); Public economics; Econometrics; Total factor productivity; Stochastic frontier analysis; Government spending; Macroeconomics; Computer science; Production (economics); Political 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008043601,0.0001635691,0.0002657814,0.0001648472,0.0001727902,0.0001611631,0.001703888,0.00003487487,0.0003169588],"category_scores_gemma":[0.01776163,0.0001092297,0.0001757583,0.00092233,0.0001486417,0.0003770631,0.0003566695,0.0001636267,0.0005145128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004031931,"about_ca_system_score_gemma":0.00002814352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001478584,"about_ca_topic_score_gemma":0.0001543218,"domain_scores_codex":[0.9901437,0.0002786985,0.0007288611,0.0008546543,0.007761005,0.0002331127],"domain_scores_gemma":[0.9963644,0.0003481606,0.0004135379,0.00135742,0.001436671,0.00007987015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001792818,0.002749929,0.02814016,0.00001081759,0.0003892842,0.00000806072,0.002570581,0.03134744,0.09543879,0.00125913,0.2724567,0.5654498],"study_design_scores_gemma":[0.0002640852,0.0001441772,0.0669701,0.00003603438,0.00004694937,0.00001142906,0.0003311859,0.009007227,0.1454037,0.001492243,0.7759597,0.0003330976],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8534905,0.0002073198,0.01025014,0.1084601,0.005508577,0.0008054009,0.00008173208,0.0000532928,0.02114286],"genre_scores_gemma":[0.9880844,0.000002949187,0.0009175863,0.0001024398,0.001110914,0.00003303348,3.711461e-7,0.00001082491,0.009737473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5651167,"threshold_uncertainty_score":0.9905122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1030888923654767,"score_gpt":0.3621254423744963,"score_spread":0.2590365500090196,"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."}}