{"id":"W4376644215","doi":"10.3390/math11102313","title":"Language Recovery in Discrete-Event Systems against Sensor Deception Attacks","year":2023,"lang":"en","type":"article","venue":"Mathematics","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Fundo para o Desenvolvimento das Ciências e da Tecnologia; King Saud University","keywords":"Nondeterministic algorithm; Supervisor; Supervisory control; Computer science; Finite-state machine; Rendering (computer graphics); Wireless sensor network; Wireless; Event (particle physics); Real-time computing; Computer security; Control (management); Artificial intelligence; Computer network; Theoretical computer science; Algorithm; Telecommunications","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":[0.0001944719,0.00009463797,0.0001433019,0.0001061488,0.00002428704,0.00003186036,0.00008939772,0.00006857561,0.00001050499],"category_scores_gemma":[0.00004656182,0.00008508159,0.00003909292,0.0002708584,0.00001337877,0.00006326412,0.00002455065,0.0001044597,0.0004496026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005409845,"about_ca_system_score_gemma":0.000004866049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006458818,"about_ca_topic_score_gemma":0.00002526729,"domain_scores_codex":[0.9993404,0.00001549371,0.0002143987,0.00008937477,0.0001422088,0.000198194],"domain_scores_gemma":[0.9996718,0.00008172394,0.00002233343,0.0001806926,0.000007492742,0.00003593001],"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":[0.000004305095,0.00007400251,0.000522688,0.002357868,0.00003853833,0.0001667792,0.01507904,0.9570007,0.01427953,0.000799866,0.007463319,0.002213318],"study_design_scores_gemma":[0.0002291966,0.00001851984,0.001228782,0.0005088945,0.000008141353,0.00001241171,0.006078942,0.9880731,0.001475695,0.0002363446,0.001849695,0.0002802981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934101,0.0001559334,0.003343304,0.00002340234,0.0005731246,0.0001717152,0.00001224896,0.0003502093,0.001960001],"genre_scores_gemma":[0.9980983,0.0002449442,0.0006689418,0.0000109685,0.0001214164,0.00002802023,0.00002440976,0.00002990173,0.0007731197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03107233,"threshold_uncertainty_score":0.5778881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01057106768267471,"score_gpt":0.2445055930478667,"score_spread":0.233934525365192,"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."}}