{"id":"W3217202204","doi":"10.1145/3489849.3489883","title":"BreachMob: Detecting Vulnerabilities in Physical Environments Using Virtual Reality","year":2021,"lang":"en","type":"article","venue":"","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Virtual reality; Computer science; Physical security; Computer security; Realization (probability); Human–computer interaction; Property (philosophy); Secure coding; Immersion (mathematics); Virtual machine; Information security; Software security assurance; Security service","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003710889,0.0001236039,0.0002159966,0.00005144961,0.00008856544,0.0001184324,0.0002943374,0.00004341322,0.0000346624],"category_scores_gemma":[0.00006955708,0.0001133518,0.0001113505,0.0002482173,0.00003506373,0.0002994591,0.0002835296,0.0002068241,0.00001525675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001070647,"about_ca_system_score_gemma":0.0000386914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001190867,"about_ca_topic_score_gemma":0.0002426164,"domain_scores_codex":[0.9985569,0.0001927481,0.0002642341,0.0004452544,0.0002633756,0.000277544],"domain_scores_gemma":[0.9994932,0.0001397944,0.00005486467,0.000241671,0.0000190465,0.00005142754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001304909,0.0008867538,0.003076253,0.00002657016,0.0001241592,0.0002694167,0.01876863,0.3505584,0.01438341,0.5537928,0.00006067327,0.05803989],"study_design_scores_gemma":[0.0001290484,0.00002155989,0.0005020509,0.00001409479,0.00000527766,0.0000155012,0.000729041,0.9902427,0.007998697,0.0001054658,0.00009837858,0.0001382211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5272923,0.000009956494,0.4719261,0.00005793161,0.00006525112,0.00001953408,2.865773e-7,0.00002413744,0.0006045196],"genre_scores_gemma":[0.9957152,9.695087e-7,0.003668285,0.0001143929,0.00008933945,0.000001923272,0.000001454123,0.000006073793,0.0004023718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6396843,"threshold_uncertainty_score":0.4622351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02452361091649149,"score_gpt":0.266263130467097,"score_spread":0.2417395195506055,"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."}}