{"id":"W2901310212","doi":"10.1145/3243734.3278495","title":"Assessing Non-Visual SSL Certificates with Desktop and Mobile Screen Readers","year":2018,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Screen reader; Computer science; Usability; Certificate; Tweaking; Mobile device; Phishing; Focus (optics); Comprehension; Point (geometry); Visualization; World Wide Web; Human–computer interaction; Internet privacy; Multimedia; Computer security; The Internet; Visually impaired; Artificial intelligence","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":[0.009051906,0.0008190212,0.0004970329,0.001254532,0.0005695492,0.002198221,0.0006271095,0.001001981,0.003854913],"category_scores_gemma":[0.05962823,0.0002787848,0.0006237137,0.0004803167,0.0008804124,0.002138238,0.001412971,0.0007135036,0.001062576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005867992,"about_ca_system_score_gemma":0.0004492469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002014124,"about_ca_topic_score_gemma":0.002579619,"domain_scores_codex":[0.992702,0.004370003,0.0007901929,0.0005246737,0.001316138,0.0002969593],"domain_scores_gemma":[0.9274237,0.05385176,0.004144856,0.003501794,0.009517194,0.001560639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005937684,0.004478485,0.3472256,0.003782993,0.0003121602,0.002001594,0.2482084,0.004866559,0.1012495,0.00123268,0.003712048,0.2769923],"study_design_scores_gemma":[0.0005713993,0.0292438,0.7251274,0.0009402324,0.0005974831,0.004652455,0.1030975,0.01771643,0.08993713,0.002327818,0.02500998,0.000778312],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939196,0.00008094854,0.002720312,0.00003773335,0.00001213424,0.0001481238,0.00004548611,0.0001050961,0.002930609],"genre_scores_gemma":[0.9935132,0.00008069288,0.004341668,0.0000572339,0.000008746505,0.0000945981,0.00006553919,0.00003106683,0.001807258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009051906,"threshold_uncertainty_score":0.04787159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03428533911034858,"score_gpt":0.3069871602283295,"score_spread":0.2727018211179809,"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."}}