{"id":"W4403663213","doi":"10.1145/3688459.3688465","title":"Eyes on the Phish(er): Towards Understanding Users' Email Processing Pattern and Mental Models in Phishing Detection","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Phishing; Computer science; Communication source; Internet privacy; World Wide Web; Relevance (law); Computer security; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008666652,0.00033517,0.0002451145,0.0003714011,0.0003126964,0.00218037,0.00062032,0.0002591526,0.000008083845],"category_scores_gemma":[0.00003189956,0.0002503105,0.00009115314,0.0003807226,0.00005349893,0.0006225742,0.001373297,0.0012187,0.000007060318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007094225,"about_ca_system_score_gemma":0.0001012815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001094588,"about_ca_topic_score_gemma":0.001188853,"domain_scores_codex":[0.9978477,0.0001241419,0.0003260151,0.000901991,0.000484655,0.0003154369],"domain_scores_gemma":[0.9992015,0.00009698085,0.000167908,0.0004397446,0.00002893,0.00006490153],"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":[0.00006353495,0.000145586,0.0004483913,0.001370643,0.0001618105,0.0000723183,0.04819624,0.01297664,0.001653654,0.02772299,0.0007102586,0.9064779],"study_design_scores_gemma":[0.0001434463,0.00005380409,0.0001349275,0.0007844643,0.00001371899,0.00001797835,0.0008646849,0.7971722,0.001957908,0.1984993,0.00003089465,0.0003266465],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1629248,0.0005200484,0.823832,0.004898872,0.002145826,0.0005035967,0.000004548401,0.0004857778,0.004684481],"genre_scores_gemma":[0.9986069,0.00008635037,0.0005529168,0.0004058869,0.0001794547,0.00005538652,0.000002388887,0.00003038297,0.00008036591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9061513,"threshold_uncertainty_score":0.9999949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07389656235103066,"score_gpt":0.2719741115689649,"score_spread":0.1980775492179342,"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."}}