{"id":"W7039603184","doi":"","title":"Money Laundering in Canada: Chasing Dirty and Dangerous Dollars","year":2022,"lang":"en","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Orthoptera Research and Taxonomy","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Money laundering; Government (linguistics); Payment; Investment (military)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001114615,0.0001007636,0.0001238731,0.0004976962,0.0003289396,0.000032531,0.0002051998,0.00002099259,0.00007805666],"category_scores_gemma":[0.00001331198,0.00005762231,0.00002994871,0.003066245,0.000024277,0.0001523566,0.0003777318,0.0002064051,7.184681e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006097966,"about_ca_system_score_gemma":0.0002684013,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9816537,"about_ca_topic_score_gemma":0.9935979,"domain_scores_codex":[0.9990046,0.0001204707,0.00007931993,0.0002666522,0.000198289,0.0003306866],"domain_scores_gemma":[0.9997283,0.00008016243,0.00003814643,0.00004810999,0.00001626615,0.00008906903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002610786,0.0001882008,0.1985156,0.00002977377,0.00004826582,0.001701594,0.002318159,0.0001123822,0.0005719658,0.0002889165,0.0001205097,0.7958435],"study_design_scores_gemma":[0.0002760176,0.000098196,0.01522758,0.000006482785,0.000004333892,0.00001361501,0.004454073,0.0001588162,0.00006132032,5.050294e-7,0.9795401,0.0001590257],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9658337,0.000006212732,0.000002662316,0.0002285466,0.000048428,0.0002350129,0.00003960314,0.0000273478,0.03357846],"genre_scores_gemma":[0.9952003,0.004608024,0.00005945807,0.00006902088,0.00002816059,0.000003523779,0.00001614754,9.657381e-7,0.00001438581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9794195,"threshold_uncertainty_score":0.252997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02464193123667386,"score_gpt":0.1892488738872103,"score_spread":0.1646069426505365,"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."}}