{"id":"W2113865496","doi":"10.1109/ares.2012.54","title":"A Personalized Whitelist Approach for Phishing Webpage Detection","year":2012,"lang":"en","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Phishing; Computer science; Web page; The Internet; Filter (signal processing); World Wide Web","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":[0.0007646898,0.00103628,0.001144001,0.004188902,0.0008159276,0.001109694,0.0008290534,0.001348163,0.002257324],"category_scores_gemma":[0.002010362,0.0004136523,0.0005896802,0.00163736,0.0003621993,0.001666138,0.0006757472,0.0008363098,0.002051359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003593329,"about_ca_system_score_gemma":0.0006342984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002000251,"about_ca_topic_score_gemma":0.004153979,"domain_scores_codex":[0.998875,0.0001646879,0.0000613763,0.0002628544,0.0005195739,0.0001166778],"domain_scores_gemma":[0.9980184,0.0004140384,0.0003623028,0.0004379607,0.000652371,0.0001150418],"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":[0.0002704248,0.0007773647,0.01058995,0.0001649079,0.0001179724,0.0002033156,0.0001684045,0.01001714,0.08061416,0.001267626,0.008082072,0.8877268],"study_design_scores_gemma":[0.0000706189,0.0009077354,0.03334464,0.00005686815,0.0002131069,0.001854741,0.0002170706,0.7810766,0.1544757,0.005018782,0.02258478,0.0001794607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1076147,0.001094889,0.8683162,0.0002435731,0.0001677424,0.0003650739,0.0004849333,0.01733361,0.004379292],"genre_scores_gemma":[0.4935318,0.0005770155,0.4928487,0.0002946477,0.0003023606,0.0002134105,0.001471933,0.0003365916,0.01042347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004188902,"threshold_uncertainty_score":0.007551491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0302681884766181,"score_gpt":0.2453131393880482,"score_spread":0.2150449509114301,"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."}}