{"id":"W4386124573","doi":"10.1109/access.2023.3308298","title":"A New Framework for Fraud Detection in Bitcoin Transactions Through Ensemble Stacking Model in Smart Cities","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"King Saud University","keywords":"Computer science; Anomaly detection; Naive Bayes classifier; Random forest; Ensemble learning; Machine learning; Artificial intelligence; Data mining; Hyperparameter; Context (archaeology); Decision tree; Heuristic; AdaBoost; Support vector machine","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":[0.001950832,0.001246595,0.001706146,0.001808561,0.0008749177,0.001950869,0.002599961,0.00194087,0.002708478],"category_scores_gemma":[0.003046812,0.0006035388,0.001604067,0.001363972,0.0009859505,0.00269508,0.001264558,0.001794676,0.0004560113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001547863,"about_ca_system_score_gemma":0.001514838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02238918,"about_ca_topic_score_gemma":0.01453472,"domain_scores_codex":[0.9990089,0.0002853605,0.00006176411,0.0002800646,0.0001732611,0.0001906051],"domain_scores_gemma":[0.9985009,0.0006378887,0.0002137899,0.00007069823,0.0004668523,0.0001099038],"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":[0.0000781282,0.0001065625,0.00545647,0.00006199936,0.0001342512,0.0002429708,0.0001539945,0.9255614,0.0007217416,0.02612026,0.001964876,0.03939727],"study_design_scores_gemma":[0.000001361293,0.000005116325,0.0001184578,0.000002908208,0.000008170011,0.000008421584,0.00000485802,0.9972011,0.00003814259,0.002488629,0.0001191638,0.000003619026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07009641,0.001252898,0.9227878,0.001078457,0.0001253793,0.00008015429,0.0002707887,0.0006518696,0.003656174],"genre_scores_gemma":[0.921637,0.001005493,0.06915016,0.0003264253,0.0002083229,0.0002028242,0.0005473059,0.00009499572,0.006827548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02238918,"threshold_uncertainty_score":0.0445177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05463698061511341,"score_gpt":0.3294634908407374,"score_spread":0.274826510225624,"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."}}