{"id":"W7126411647","doi":"10.21428/594757db.3e4f0dfb","title":"BankGAN: A Generative Model for Synthetic FinancialTransactions","year":2024,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Verafin (Canada); Memorial University of Newfoundland","funders":"","keywords":"Synthetic data; Generative model; Generative grammar; Database transaction; Transaction data; Data modeling; Recurrent neural network","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":[0.001071541,0.0005602377,0.0004082285,0.0004722326,0.000189384,0.0005702116,0.001188212,0.0007478049,0.002874855],"category_scores_gemma":[0.003404964,0.0004259144,0.0006711691,0.0004434974,0.0007161535,0.0008577785,0.0006781937,0.001198681,0.0005450397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008519572,"about_ca_system_score_gemma":0.0004640659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004343945,"about_ca_topic_score_gemma":0.007623432,"domain_scores_codex":[0.9996718,0.0001323875,0.00001377966,0.00008680975,0.00006167126,0.00003341724],"domain_scores_gemma":[0.9986217,0.0009759138,0.000102283,0.0001513265,0.0001121923,0.00003671117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008527605,0.00003308911,0.002028364,0.00003679217,0.00003014185,0.00008024631,0.0000622555,0.9578872,0.001653175,0.01889769,0.001627614,0.0175782],"study_design_scores_gemma":[0.000002136757,0.000006329921,0.0001105372,0.000002460837,0.000002105717,0.0000120607,0.000003039059,0.9957858,0.0002612595,0.003543003,0.0002686417,0.00000265213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08498568,0.000385372,0.9067574,0.0007066157,0.0001074806,0.0001090348,0.001746049,0.001330761,0.003871632],"genre_scores_gemma":[0.9066082,0.0003248388,0.08358821,0.0002916953,0.00004806343,0.0002429988,0.002347529,0.0001711614,0.006377203],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004343945,"threshold_uncertainty_score":0.009617329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0456538863630695,"score_gpt":0.2931879771982809,"score_spread":0.2475340908352114,"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."}}