{"id":"W2164600404","doi":"10.1109/ssiri.2010.17","title":"PhishTester: Automatic Testing of Phishing Attacks","year":2010,"lang":"en","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Phishing; Computer science; Leverage (statistics); Scripting language; Computer security; World Wide Web; Information sensitivity; Web application; The Internet; Artificial intelligence","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":[0.001253623,0.001083794,0.0005821701,0.001614183,0.0002515288,0.0006480563,0.001400542,0.001123649,0.002260396],"category_scores_gemma":[0.007914077,0.0005218337,0.0005213401,0.0005949297,0.0005098221,0.001465914,0.0008204717,0.0007340211,0.001173886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004012656,"about_ca_system_score_gemma":0.0007729679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002307618,"about_ca_topic_score_gemma":0.001938363,"domain_scores_codex":[0.9977782,0.0006156334,0.0001716425,0.0004839851,0.0008019524,0.000148619],"domain_scores_gemma":[0.9933574,0.003327174,0.0008530825,0.001386856,0.0009049758,0.0001706246],"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":[0.001514112,0.001468535,0.1044307,0.00108276,0.0003697526,0.0015579,0.001139566,0.07879484,0.18151,0.004514313,0.01852191,0.6050956],"study_design_scores_gemma":[0.00008902625,0.0006775645,0.02061374,0.00006615378,0.00005663647,0.0009126266,0.0001314749,0.8709379,0.09892767,0.002395557,0.005134656,0.00005693302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2765452,0.0003635064,0.519885,0.0002366996,0.00007009226,0.0004111944,0.00151726,0.1980216,0.002949385],"genre_scores_gemma":[0.8580649,0.0000976774,0.1373089,0.0001150906,0.00001561672,0.0001671254,0.00149078,0.001016895,0.001722965],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002307618,"threshold_uncertainty_score":0.007561743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02230607588746938,"score_gpt":0.2460909461809874,"score_spread":0.223784870293518,"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."}}