{"id":"W2943539799","doi":"10.1109/iscas.2019.8702440","title":"Towards System Level Security Analysis of Artificial Pancreas Via UPPAAL-SMC","year":2019,"lang":"en","type":"article","venue":"","topic":"Diabetes Management and Research","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Reliability (semiconductor); Artificial pancreas; Adversary; Automaton; Control (management); Replay attack; Control system; Computer security; Artificial intelligence; Engineering","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":[0.00113358,0.0007111063,0.0006146108,0.0006246307,0.0004280007,0.001075401,0.0007700216,0.0006218093,0.002342438],"category_scores_gemma":[0.003008207,0.0003027597,0.001141353,0.000275113,0.0009159266,0.0008293118,0.0009143153,0.001229152,0.000292802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005858746,"about_ca_system_score_gemma":0.001263415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00413332,"about_ca_topic_score_gemma":0.002058556,"domain_scores_codex":[0.9991844,0.0002232325,0.00003317318,0.0001075318,0.0003446431,0.000106965],"domain_scores_gemma":[0.9988154,0.0006022495,0.0001444469,0.0001486498,0.0002618717,0.0000274631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007223211,0.00004446465,0.001168896,0.0001174101,0.00005509934,0.0001884175,0.0001076482,0.9286269,0.00775221,0.044701,0.0003263365,0.01683941],"study_design_scores_gemma":[0.000003652936,0.00001917184,0.0000581069,0.000005557561,0.000009428618,0.00001274199,0.000004897188,0.9924178,0.001527688,0.005504332,0.0004340096,0.000002554724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02057115,0.0001131005,0.9757087,0.00007532662,0.00002124881,0.00004684841,0.00004313722,0.0005592284,0.002861157],"genre_scores_gemma":[0.8377135,0.0002837355,0.1592936,0.00008386758,0.00002639887,0.0001752186,0.000098636,0.000125307,0.002199803],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00413332,"threshold_uncertainty_score":0.008218527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03308456874771735,"score_gpt":0.3032493673487277,"score_spread":0.2701647986010103,"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."}}