{"id":"W4388916527","doi":"10.1109/pst58708.2023.10320177","title":"A Comparison of Machine Learning Algorithms for Multilingual Phishing Detection","year":2023,"lang":"en","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Phishing; Computer science; Machine learning; Harm; Artificial intelligence; Transformer; Algorithm; World Wide Web; The Internet; Engineering","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":[0.008624777,0.002218742,0.001751869,0.005070784,0.001017033,0.002097066,0.001402976,0.001811531,0.001474995],"category_scores_gemma":[0.01540366,0.0003738856,0.001504055,0.002494689,0.0003915602,0.002784725,0.001325783,0.001845288,0.001355553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001584711,"about_ca_system_score_gemma":0.001569219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01213922,"about_ca_topic_score_gemma":0.009859031,"domain_scores_codex":[0.9950613,0.002036125,0.0005857626,0.0007994637,0.001110979,0.0004062874],"domain_scores_gemma":[0.98671,0.008379946,0.000485199,0.001002423,0.003049094,0.0003733059],"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":[0.002925329,0.001446927,0.05160893,0.0008341559,0.002078296,0.0001998108,0.0002487549,0.2220669,0.002978778,0.002240879,0.01312604,0.7002451],"study_design_scores_gemma":[0.00006551674,0.0009371437,0.01077405,0.0001176156,0.0002973207,0.000167228,0.0003396013,0.9779588,0.003869661,0.002017287,0.003381277,0.00007436462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7635844,0.04043959,0.1618166,0.002745618,0.001629834,0.0003604229,0.00334254,0.00872623,0.01735469],"genre_scores_gemma":[0.8908556,0.004229923,0.09505671,0.0003940611,0.0002826121,0.0001427618,0.005251238,0.0002759056,0.003511188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01213922,"threshold_uncertainty_score":0.04561275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06505257610855099,"score_gpt":0.3477292427535537,"score_spread":0.2826766666450027,"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."}}