{"id":"W4417508086","doi":"10.1007/s11235-025-01388-7","title":"URLMoE: leveraging multi-head attention and expert specialization for robust malicious URL classification","year":2025,"lang":"en","type":"article","venue":"Telecommunication Systems","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Malware; Benchmark (surveying); Identification (biology); Convolutional neural network; Fuse (electrical); Exploit; Focus (optics); Botnet","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":[0.00197833,0.002131531,0.002576088,0.004685619,0.0008799986,0.001375636,0.002299856,0.003187761,0.004272139],"category_scores_gemma":[0.0038576,0.0006229666,0.001216171,0.001593803,0.0004466518,0.002404132,0.002812695,0.00177154,0.004362043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006547282,"about_ca_system_score_gemma":0.001183265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007916978,"about_ca_topic_score_gemma":0.0183348,"domain_scores_codex":[0.998235,0.0002738928,0.00008056659,0.0005596688,0.0004905809,0.0003602627],"domain_scores_gemma":[0.9974618,0.0008827834,0.0001642005,0.0004935216,0.00071113,0.0002865333],"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":[0.000901401,0.001219884,0.008667292,0.0001876685,0.0003052439,0.0004335672,0.0001343982,0.01321705,0.03638244,0.0006866797,0.04242679,0.8954375],"study_design_scores_gemma":[0.0000578804,0.0003322178,0.005368663,0.00001849341,0.0001284329,0.0003808234,0.00007340551,0.9639162,0.022827,0.002277961,0.004569593,0.00004925399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2522467,0.004570332,0.6420677,0.001431778,0.001145706,0.0006718395,0.003468032,0.08331905,0.01107872],"genre_scores_gemma":[0.7649177,0.0005459073,0.2033084,0.001556354,0.0008139178,0.000165498,0.007123692,0.001215918,0.02035266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007916978,"threshold_uncertainty_score":0.01574183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1014621485772353,"score_gpt":0.3259107990991861,"score_spread":0.2244486505219509,"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."}}