{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003833696,0.0006358539,0.0006814782,0.001245611,0.001200479,0.003437885,0.001181051,0.0009835843,0.001265596],"category_scores_gemma":[0.02370357,0.0006790765,0.0005708936,0.0005117225,0.003056852,0.00639004,0.003574381,0.002171575,0.0005196384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001213676,"about_ca_system_score_gemma":0.001659322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004748398,"about_ca_topic_score_gemma":0.00378718,"domain_scores_codex":[0.9904265,0.003156693,0.001028955,0.001522158,0.003098411,0.0007672725],"domain_scores_gemma":[0.9799371,0.006892311,0.003093529,0.006754025,0.002762232,0.0005606288],"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":[0.005757087,0.001082081,0.1096078,0.001005387,0.0003570756,0.004956461,0.01637073,0.06912149,0.1253805,0.166074,0.003036329,0.4972512],"study_design_scores_gemma":[0.0001951828,0.001511525,0.01982659,0.0005799677,0.0003103476,0.00148147,0.002940719,0.3901796,0.4335665,0.1322728,0.01657803,0.0005572975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5872203,0.00098195,0.3932154,0.0007669659,0.0001797749,0.0003957717,0.0003540958,0.008449948,0.008435826],"genre_scores_gemma":[0.9718005,0.0001084746,0.02685303,0.0001041363,0.00002334764,0.00005670775,0.00007329876,0.0001074125,0.0008730032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004748398,"threshold_uncertainty_score":0.02027476,"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."}}