{"id":"W4387385059","doi":"10.2139/ssrn.4580004","title":"Emerging Digital Technologies to Improve Tax Compliance and Administration Efficiency: A Systematic Literature Review","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Taxation and Compliance Studies","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Compliance (psychology); Business; Tax administration; Process (computing); Protocol (science); Public economics; Administration (probate law); Accounting; Economics; Tax reform; Computer science; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009742004,0.000682231,0.002656263,0.007755306,0.0003091057,0.00251749,0.001078628,0.001464948,0.006375717],"category_scores_gemma":[0.0402771,0.000566347,0.003438318,0.009309019,0.001056948,0.002619056,0.001160484,0.001333588,0.0004423492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002171919,"about_ca_system_score_gemma":0.01031554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003915512,"about_ca_topic_score_gemma":0.014106,"domain_scores_codex":[0.9937099,0.002336877,0.001802377,0.0005372399,0.001416981,0.000196608],"domain_scores_gemma":[0.9406301,0.04702602,0.008427504,0.0007693704,0.002737627,0.0004093715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0005956684,0.0002788363,0.007558677,0.5361516,0.009476506,0.0001415034,0.0004355392,0.0005924941,0.0002266071,0.002429694,0.004315274,0.4377977],"study_design_scores_gemma":[0.0006780362,0.001103785,0.03210664,0.8404812,0.05683826,0.0005488724,0.001202707,0.0005884707,0.0005542432,0.002370231,0.06344325,0.0000843238],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003664297,0.9940584,0.0003208758,0.0005023546,0.00009269945,0.0001662472,0.0003376895,0.000007419121,0.0008500153],"genre_scores_gemma":[0.04310829,0.9543816,0.001173375,0.0007146883,0.0001167605,0.00016567,0.0001881479,0.000005627149,0.0001458869],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009742004,"threshold_uncertainty_score":0.05152124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01896924496573881,"score_gpt":0.2541945519698879,"score_spread":0.2352253070041491,"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."}}