{"id":"W2940610044","doi":"10.1108/jmlc-09-2017-0048","title":"Anti-money laundering and moral intensity in suspicious activity reporting","year":2018,"lang":"en","type":"article","venue":"Journal of Money Laundering Control","topic":"Crime, Illicit Activities, and Governance","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Roads University","funders":"","keywords":"Money laundering; Compliance (psychology); Database transaction; Business; Accounting; Value (mathematics); Public relations; Originality; Political science; Psychology; Law; Finance; Social psychology; Computer science","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":[0.007716368,0.0002049338,0.0002211187,0.001317056,0.001720155,0.003990021,0.0007713495,0.0005835613,0.001965658],"category_scores_gemma":[0.03159874,0.0002738047,0.0002128238,0.0007131296,0.004052659,0.001617509,0.002070688,0.001690694,0.0001671335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004054488,"about_ca_system_score_gemma":0.003019519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01215326,"about_ca_topic_score_gemma":0.02516439,"domain_scores_codex":[0.9916353,0.004625767,0.0004551197,0.0005230152,0.001890426,0.0008703388],"domain_scores_gemma":[0.9291661,0.02323582,0.0375418,0.002291583,0.004494019,0.0032708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002484508,0.0006547088,0.9357122,0.0001172544,0.00006760073,0.0002668459,0.02775487,0.0005788804,0.001481164,0.006053035,0.000718536,0.02634639],"study_design_scores_gemma":[0.00001079297,0.0001922786,0.9539896,0.00008512693,0.00003512648,0.0001547173,0.03821067,0.001857353,0.0005247758,0.002582418,0.002303621,0.00005350487],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936755,0.00004695818,0.0008905014,0.0005048952,0.000007464443,0.00002732485,0.00001218769,0.000004863041,0.004830255],"genre_scores_gemma":[0.9992917,0.00002183602,0.0003716013,0.0000666362,0.000005591067,0.00000896887,0.00001048142,0.000001370628,0.0002219081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01215326,"threshold_uncertainty_score":0.04080856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04269631780880192,"score_gpt":0.3123826285258935,"score_spread":0.2696863107170916,"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."}}