{"id":"W4407614550","doi":"10.21203/rs.3.rs-6026136/v1","title":"Real-Time Financial Fraud Detection Using Adaptive Graph Neural Networks and Federated Learning","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Financial fraud; Artificial neural network; Adaptive learning; Graph; Artificial intelligence; Machine learning; Business; Accounting; Theoretical 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":[0.002105671,0.000941233,0.001239631,0.003185167,0.0006130224,0.001635302,0.001832028,0.001522058,0.001115176],"category_scores_gemma":[0.008710157,0.0003422202,0.000630411,0.002090188,0.0005548304,0.002789259,0.001297931,0.001312161,0.0003974036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001094566,"about_ca_system_score_gemma":0.000815394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004557647,"about_ca_topic_score_gemma":0.005017413,"domain_scores_codex":[0.9989009,0.0003544725,0.00006602922,0.0002859595,0.0002406886,0.0001519375],"domain_scores_gemma":[0.9964229,0.001592505,0.0004873289,0.0006771243,0.0006387669,0.0001811824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001374818,0.001236927,0.02676232,0.000114648,0.0003325261,0.000317035,0.0001018759,0.415702,0.004884593,0.00546405,0.009393746,0.5343155],"study_design_scores_gemma":[0.000006531198,0.00001944737,0.000676544,0.000002463592,0.000007617553,0.0000229672,0.000009389322,0.9956986,0.0005402414,0.002894231,0.0001188211,0.000003084569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.426968,0.001299384,0.5614917,0.002022378,0.0004933092,0.0001625471,0.001003801,0.003852554,0.002706196],"genre_scores_gemma":[0.9481559,0.000118028,0.04984733,0.0001062532,0.00009260839,0.00002958463,0.000539609,0.00003990603,0.00107079],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004557647,"threshold_uncertainty_score":0.011136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05770605325976844,"score_gpt":0.3612099117997352,"score_spread":0.3035038585399668,"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."}}