{"id":"W3130217728","doi":"10.2139/ssrn.3722391","title":"A Machine Learning Attack on Illegal Trading","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Business; Computer security; 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":[0.001676628,0.000397834,0.0006434344,0.0009665512,0.001021776,0.001378395,0.0007602209,0.002214785,0.003222494],"category_scores_gemma":[0.01380446,0.0001811495,0.0006198726,0.000607051,0.001296187,0.002178962,0.001842322,0.001841855,0.000430307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005617592,"about_ca_system_score_gemma":0.0004278985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001235848,"about_ca_topic_score_gemma":0.0008869265,"domain_scores_codex":[0.998673,0.0005257446,0.00005148493,0.0001520121,0.0004194857,0.0001783676],"domain_scores_gemma":[0.993022,0.004631578,0.0004496618,0.001136275,0.0005098865,0.0002505948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001471661,0.0004954852,0.01709922,0.0001619095,0.0002588862,0.00274001,0.0007592989,0.2381445,0.01206431,0.3884373,0.02790313,0.3104643],"study_design_scores_gemma":[0.00003301071,0.00008005589,0.0009604723,0.00002071508,0.00001842914,0.0004233386,0.00005388021,0.923662,0.002122505,0.07054491,0.002067971,0.0000126263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5389608,0.0004382231,0.3954866,0.007918466,0.0005285084,0.0001652029,0.0003335085,0.001302023,0.05486668],"genre_scores_gemma":[0.9759644,0.0001226774,0.0177599,0.0002706483,0.0001080705,0.00002817771,0.00008522291,0.00003899862,0.00562195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003222494,"threshold_uncertainty_score":0.01078033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1301502634625518,"score_gpt":0.3937986907550581,"score_spread":0.2636484272925063,"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."}}