{"id":"W4408860251","doi":"10.1109/access.2025.3555157","title":"SoK: Grouping Spam and Phishing Email Threats for Smarter Security","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Phishing; Computer science; Computer security; Internet privacy; World Wide Web; The Internet","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01262021,0.00177992,0.001662838,0.03067498,0.004059675,0.008573606,0.001881533,0.002501311,0.005391526],"category_scores_gemma":[0.063797,0.0006805375,0.001926985,0.01627662,0.002688672,0.01626645,0.006791466,0.001753884,0.004589856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00201453,"about_ca_system_score_gemma":0.004039334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002525774,"about_ca_topic_score_gemma":0.005112146,"domain_scores_codex":[0.983713,0.007446815,0.001950711,0.002062069,0.003987977,0.0008393613],"domain_scores_gemma":[0.9438646,0.02406223,0.009245798,0.01131091,0.009361027,0.002155469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009824057,0.0006541799,0.1183918,0.01305723,0.0008933669,0.0004374328,0.02273277,0.00440808,0.008041936,0.03268828,0.06465995,0.7330526],"study_design_scores_gemma":[0.0005017198,0.003048116,0.2728627,0.01307688,0.002049679,0.002550225,0.08264118,0.05304829,0.01964723,0.1442087,0.4055305,0.0008347342],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4657702,0.02134762,0.3483032,0.01547168,0.002382892,0.01262778,0.02942922,0.03112354,0.07354388],"genre_scores_gemma":[0.4541068,0.008410735,0.4823826,0.002721097,0.001043082,0.005431862,0.03349779,0.001647471,0.01075862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03067498,"threshold_uncertainty_score":0.06674284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03009676864490229,"score_gpt":0.3259160867546236,"score_spread":0.2958193181097213,"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."}}