{"id":"W2595864349","doi":"","title":"Cyber Laundering: An Analysis of Typology and Techniques","year":2008,"lang":"en","type":"article","venue":"International Journal of Criminal Justice Sciences","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"The Internet; Cyberspace; Law enforcement; Money laundering; Order (exchange); Enforcement; Business; Internet privacy; Computer security; Law; Finance; Political science; Computer science; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006939194,0.0007342656,0.0006608208,0.01783844,0.00429154,0.009500388,0.001908803,0.00147628,0.009726381],"category_scores_gemma":[0.02757832,0.0004126008,0.001118467,0.02160457,0.005954955,0.01073376,0.004247321,0.00172107,0.001126415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006251444,"about_ca_system_score_gemma":0.002997974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00440783,"about_ca_topic_score_gemma":0.003570679,"domain_scores_codex":[0.988311,0.005858246,0.0009645787,0.001163724,0.002817215,0.000885284],"domain_scores_gemma":[0.9602581,0.02575176,0.004534903,0.002960654,0.005629732,0.0008648621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002133646,0.0003836694,0.2110736,0.001710305,0.00007815735,0.001969732,0.3110516,0.001042973,0.001756009,0.2701701,0.01484605,0.1857043],"study_design_scores_gemma":[0.0000314399,0.0001762881,0.1217421,0.003090199,0.00008800987,0.004861832,0.5288523,0.01308934,0.001625126,0.139644,0.1866612,0.000138116],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7505087,0.00804832,0.05616282,0.00444576,0.0002695537,0.00186586,0.002519462,0.0005441498,0.1756354],"genre_scores_gemma":[0.9372646,0.002895288,0.04632088,0.0003191539,0.00008000532,0.001485237,0.002290918,0.0002189562,0.009125058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01783844,"threshold_uncertainty_score":0.04535758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06461751377662919,"score_gpt":0.3586163771075424,"score_spread":0.2939988633309132,"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."}}