{"id":"W2172144081","doi":"10.5539/ibr.v6n6p129","title":"The Impact of Overhead Cost Budgeting on the Annual Imprest Expenditures of State Ministries, Departments and Agencies (MDAs): A Study from Cross River State, Nigeria","year":2013,"lang":"en","type":"article","venue":"International Business Research","topic":"Accounting and Organizational Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Overhead (engineering); Government (linguistics); Business; State (computer science); Government budget; Public economics; Finance; Economics; Operations management; Actuarial science; Computer science; Public finance; Macroeconomics","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":[0.001010232,0.0001519448,0.0001573366,0.0007782777,0.0007490952,0.0009607921,0.0002599509,0.0002920473,0.001698878],"category_scores_gemma":[0.004153991,0.000318814,0.0002016866,0.001167681,0.0004423049,0.000750265,0.0005434442,0.000677879,0.0001988598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001205722,"about_ca_system_score_gemma":0.001372625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02421933,"about_ca_topic_score_gemma":0.06224351,"domain_scores_codex":[0.9993203,0.000260804,0.00008907093,0.00004926221,0.0001056,0.0001750222],"domain_scores_gemma":[0.9954874,0.00140809,0.002171777,0.00008680674,0.0003627982,0.00048317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004882834,0.0001928602,0.9823673,0.00006617781,0.00001432594,0.0007854422,0.01032226,0.00006127425,0.000331219,0.0002238013,0.0002713857,0.005315153],"study_design_scores_gemma":[0.000002024404,0.0001429249,0.9703916,0.00005289317,0.00001306894,0.0004162283,0.0278908,0.00008051834,0.00007877895,0.00002444614,0.0009004818,0.000006276773],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995493,0.0000509303,0.000007035896,0.00005644195,0.00000109855,0.000003161835,0.00002621147,1.846606e-7,0.0003056876],"genre_scores_gemma":[0.99939,0.0002355112,0.00003312502,0.00002879969,0.000002168896,0.000005357545,0.00004072776,5.390563e-7,0.0002637593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02421933,"threshold_uncertainty_score":0.04815674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03367824089298098,"score_gpt":0.3420926645801646,"score_spread":0.3084144236871836,"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."}}