{"id":"W4388106384","doi":"10.5430/afr.v12n4p62","title":"Money Laundering Prevention through Regulatory Technology and Internal Audit Function in Indonesia Banking Sector","year":2023,"lang":"en","type":"article","venue":"Accounting and Finance Research","topic":"Crime, Illicit Activities, and Governance","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Teknologi MARA","keywords":"Money laundering; Business; Audit; Finance; Cash; Financial services; Accounting; Terrorism; Government (linguistics); Internal audit; Function (biology)","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":[0.00155777,0.0002088178,0.0001731425,0.0007025188,0.001118722,0.002672026,0.0005176103,0.0007119088,0.003488221],"category_scores_gemma":[0.003239032,0.0001490032,0.0001633943,0.0005484408,0.0009295988,0.001113124,0.001177046,0.001029253,0.0006461888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001750785,"about_ca_system_score_gemma":0.005495525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005575548,"about_ca_topic_score_gemma":0.007961024,"domain_scores_codex":[0.9988834,0.0004430314,0.00007114881,0.00007160392,0.0002639539,0.0002667344],"domain_scores_gemma":[0.9966497,0.0007679109,0.001328885,0.0001447711,0.0005809877,0.0005277452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006186964,0.003221615,0.3278458,0.002064253,0.00004591756,0.00388485,0.02965911,0.002737661,0.01029606,0.02368752,0.02050661,0.5754319],"study_design_scores_gemma":[0.0001000885,0.001435918,0.7867074,0.003381634,0.0001897593,0.002670595,0.0705642,0.008483731,0.01107437,0.00642876,0.1088456,0.0001180445],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9329392,0.002730413,0.001165809,0.006830517,0.00006868075,0.0001427755,0.0000629295,0.00007461903,0.05598493],"genre_scores_gemma":[0.9929471,0.001497742,0.000713552,0.0004498561,0.0000143339,0.0000224605,0.00002178799,0.000006541092,0.004326606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005575548,"threshold_uncertainty_score":0.01270288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06238499684574255,"score_gpt":0.3606903681287041,"score_spread":0.2983053712829615,"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."}}