{"id":"W1995554356","doi":"10.1145/1978942.1979244","title":"Does domain highlighting help people identify phishing sites?","year":2011,"lang":"en","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Phishing; Legitimacy; Domain (mathematical analysis); Exploit; Computer science; World Wide Web; Internet privacy; Domain name; Web page; Computer security; The Internet; Political science; Law","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":[0.004626465,0.0005725823,0.0005954176,0.001351986,0.0009681345,0.001755529,0.0003308182,0.00180402,0.006510728],"category_scores_gemma":[0.0293729,0.0002801303,0.0003690012,0.0006384772,0.0007291707,0.004101004,0.0009695977,0.0007215576,0.002717844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002432957,"about_ca_system_score_gemma":0.000558514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009188937,"about_ca_topic_score_gemma":0.001400208,"domain_scores_codex":[0.9983611,0.0009895345,0.00007190773,0.0001681411,0.0002216101,0.0001877179],"domain_scores_gemma":[0.9832231,0.01147177,0.001851158,0.000987003,0.001463515,0.001003402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009425872,0.001668808,0.3946095,0.001260138,0.0001419903,0.0004922024,0.03429061,0.0004114598,0.01579276,0.001511988,0.01895131,0.5299266],"study_design_scores_gemma":[0.0005798353,0.006210316,0.6825276,0.001449673,0.00108843,0.00536669,0.1534926,0.01533565,0.0275527,0.01499607,0.09085695,0.0005434766],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9716271,0.00126154,0.004114083,0.006454598,0.0001241571,0.0002044295,0.0001611506,0.0005138764,0.01553897],"genre_scores_gemma":[0.9920265,0.0006073813,0.005028666,0.000959487,0.00004953105,0.00004841459,0.00006594859,0.00002748669,0.001186649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006510728,"threshold_uncertainty_score":0.02446741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02471575098055676,"score_gpt":0.2357652450595044,"score_spread":0.2110494940789476,"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."}}