{"id":"W2968172377","doi":"10.1145/3343737.3343739","title":"Using Inputs and Context to Verify User Intentions in Internet Services","year":2019,"lang":"en","type":"article","venue":"","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Hypervisor; Computer science; Context (archaeology); Malware; Computer security; The Internet; Service (business); World Wide Web; Server; Operating system; Virtualization; Cloud computing","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":[0.000154683,0.00006162632,0.0000831488,0.0001157585,0.00002502685,0.0001672065,0.000352973,0.00003360081,0.00003472821],"category_scores_gemma":[0.000007417243,0.0000604015,0.00001470162,0.000258998,0.000009064911,0.0003537527,0.0003327412,0.0000744815,0.0000941248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002509348,"about_ca_system_score_gemma":0.00001590943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004127677,"about_ca_topic_score_gemma":0.0002218295,"domain_scores_codex":[0.9993604,0.00002692319,0.0001490524,0.0002444904,0.00009730401,0.0001218162],"domain_scores_gemma":[0.9996083,0.00004053803,0.00003056025,0.000225974,0.00004600864,0.00004856194],"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":[0.00001634903,0.0001383574,0.1914797,0.0001318341,0.00002609757,0.000006339163,0.01865636,0.0006512399,0.01092377,0.7419652,0.0003581239,0.03564667],"study_design_scores_gemma":[0.0004984332,0.00006497928,0.04380444,0.0002202321,0.000002132323,0.00001986485,0.0007975536,0.9321487,0.003748554,0.0009604807,0.01745458,0.0002800441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7257665,0.00002763037,0.2717059,0.0005170441,0.0002712546,0.000101576,1.85518e-7,0.00004701105,0.001562859],"genre_scores_gemma":[0.9718054,0.00000169408,0.02634708,0.001646097,0.00001219422,0.000002016128,3.929358e-7,0.000002896824,0.0001822156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9314975,"threshold_uncertainty_score":0.2463102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03325638221385967,"score_gpt":0.2857379541343466,"score_spread":0.2524815719204869,"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."}}