{"id":"W7126388153","doi":"10.21428/594757db.fca1c492","title":"Handling Concept Drift in Fraud Detection: A Replication Study","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Replication (statistics); Replicate; Concept drift; Recall; Simple (philosophy)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1433071,0.001742502,0.002036628,0.003842584,0.00221864,0.004745299,0.004866559,0.003526269,0.002046898],"category_scores_gemma":[0.4377779,0.0008839917,0.005039764,0.003233571,0.002967192,0.009143592,0.0032918,0.004717317,0.00100101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002472757,"about_ca_system_score_gemma":0.003227799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005117369,"about_ca_topic_score_gemma":0.002363107,"domain_scores_codex":[0.8909201,0.07853542,0.007460304,0.009792197,0.01219467,0.001097205],"domain_scores_gemma":[0.3941603,0.3436942,0.02192942,0.1738536,0.063673,0.002689532],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01549006,0.01296871,0.3494767,0.008001219,0.009599892,0.002104177,0.01587127,0.03066742,0.01223558,0.01960293,0.0347099,0.4892723],"study_design_scores_gemma":[0.01051199,0.02967148,0.1619109,0.003734821,0.01467017,0.007547792,0.01685693,0.4890182,0.05512609,0.1142606,0.09514374,0.001547256],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8208813,0.01202931,0.1418764,0.00727405,0.00214779,0.006079183,0.002351079,0.00128506,0.006075837],"genre_scores_gemma":[0.9111563,0.001251178,0.07983937,0.00192413,0.0007846754,0.00171052,0.001885938,0.0002079722,0.001240002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8566929,"threshold_uncertainty_score":0.7578894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01286573610785745,"score_gpt":0.3056526419245791,"score_spread":0.2927869058167216,"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."}}