{"id":"W2963977511","doi":"10.25105/jipak.v3i1.4437","title":"OPTIMALISASI PERAN DANA BAGI HASIL (DBH) DALAM PEMBANGUNAN DAERAH","year":2019,"lang":"en","type":"article","venue":"JURNAL INFORMASI PERPAJAKAN AKUNTANSI DAN KEUANGAN PUBLIK","topic":"Economic Growth and Fiscal Policies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Revenue sharing; Revenue; Balance (ability); Quarter (Canadian coin); Fiscal capacity; Business; Finance; Fiscal year; Fiscal policy; Economic policy; Economics; Political science; Macroeconomics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001069196,0.0007443374,0.001256637,0.0009295995,0.000435492,0.001086897,0.001320301,0.0004370225,0.0009144408],"category_scores_gemma":[0.0001768234,0.0008102952,0.0006384836,0.0006749411,0.0002765228,0.002772704,0.0003308194,0.001014007,0.002450242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004634055,"about_ca_system_score_gemma":0.0001721272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002689066,"about_ca_topic_score_gemma":0.0001548236,"domain_scores_codex":[0.9953066,0.00003803298,0.002024515,0.0009074472,0.0002035845,0.001519862],"domain_scores_gemma":[0.9968358,0.00009969736,0.0009056678,0.001259149,0.0001388183,0.000760853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008145813,0.000164822,0.612018,0.000125226,0.0002011908,0.00002162474,0.003116895,0.0002082847,0.0001070214,0.3764242,0.005776023,0.001755295],"study_design_scores_gemma":[0.002858125,0.0004441755,0.3715312,0.00006328954,0.00002936821,0.0002748894,0.002194463,0.005141601,0.0002483469,0.001940122,0.6136602,0.001614184],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6640378,0.0005913042,0.00006875267,0.001654094,0.001199897,0.0004445541,0.0001541264,0.0001788568,0.3316706],"genre_scores_gemma":[0.979573,0.0001320707,0.0004323617,0.003621372,0.0006308017,0.00004169742,0.0002511945,0.0001332196,0.01518436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6078842,"threshold_uncertainty_score":0.9999989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01710030286345748,"score_gpt":0.197098768869562,"score_spread":0.1799984660061046,"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."}}