{"id":"W2046047370","doi":"10.1108/13685200310809662","title":"Using confiscated money","year":2003,"lang":"en","type":"article","venue":"Journal of Money Laundering Control","topic":"Crime, Illicit Activities, and Governance","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Money laundering; Restitution; Task force; Convention; Terrorism; Compensation (psychology); Subject (documents); Business; Finance; Law; Economics; Political science; Public administration","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":[0.002929834,0.0005531984,0.0003230657,0.002736379,0.005005751,0.007096707,0.00181909,0.003121302,0.005835425],"category_scores_gemma":[0.004813493,0.0002496261,0.0005602943,0.002959677,0.01040052,0.006070918,0.003083172,0.001672508,0.001785114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009854424,"about_ca_system_score_gemma":0.01308237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.154478,"about_ca_topic_score_gemma":0.1859792,"domain_scores_codex":[0.9951718,0.0007365479,0.0001414567,0.000256752,0.002833807,0.0008595971],"domain_scores_gemma":[0.9980217,0.0005693786,0.0002256577,0.0003623497,0.0006611399,0.000159769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001479206,0.00003457337,0.0009726881,0.0001439088,0.00001138062,0.0003383897,0.006677988,0.0004161665,0.0006538165,0.8530089,0.03800424,0.09972312],"study_design_scores_gemma":[0.000003166552,0.00003560782,0.001070278,0.0005649948,0.00001775678,0.0007006222,0.003047128,0.000512288,0.002500071,0.03255906,0.9589582,0.0000308522],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02273073,0.03276339,0.04315251,0.03054617,0.002250273,0.0001665722,0.0001527525,0.0002703958,0.8679671],"genre_scores_gemma":[0.430493,0.05348912,0.01985335,0.01671299,0.00143039,0.0002109046,0.0002154482,0.0003085173,0.4772863],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.154478,"threshold_uncertainty_score":0.3071577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05068206577480663,"score_gpt":0.3147368650465664,"score_spread":0.2640547992717598,"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."}}