{"id":"W2899892964","doi":"10.1155/2018/4329053","title":"Performance Analysis of Switched Control Systems Under Common‐source Digital Upsets Modeled by MDHMM","year":2018,"lang":"en","type":"article","venue":"Complexity","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Fundamental Research Funds for the Central Universities; Civil Aviation University of China; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Reliability (semiconductor); Markov chain; Control (management); Control system; Complex system; Markov process; Reliability engineering; Digital control; Control engineering; Electronic engineering; Engineering; Artificial intelligence; Machine learning; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001262581,0.0001306961,0.0003894678,0.00008624519,0.00006218642,0.00004484595,0.0001643059,0.00006864799,0.00003653779],"category_scores_gemma":[0.00001682571,0.0001229298,0.00009252042,0.0004116932,0.0001740506,0.0001990831,0.00002319554,0.00007906372,0.00001487174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007141487,"about_ca_system_score_gemma":0.000008004657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006948839,"about_ca_topic_score_gemma":0.00002526371,"domain_scores_codex":[0.9991692,0.00002141689,0.0003071251,0.0001533908,0.0001470969,0.0002017727],"domain_scores_gemma":[0.9993511,0.00004494937,0.00006605837,0.0003415619,0.0001357009,0.00006061495],"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":[0.00002728549,0.00003512321,0.005706707,0.00005803655,0.0003365217,7.399108e-8,0.0001304911,0.9918726,0.0004390955,0.0003032608,0.0008022003,0.0002886097],"study_design_scores_gemma":[0.000355246,0.00003994656,0.006946969,0.00001565903,0.0001149261,7.856928e-7,0.00005856624,0.9917162,0.0001823005,0.0001161231,0.0003217881,0.0001314683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.651923,0.0000588313,0.34541,0.00002078563,0.00008867419,0.0001314287,0.0000856462,0.0001190172,0.00216256],"genre_scores_gemma":[0.9995518,0.00001304923,0.0001615588,0.00002186668,0.00002920291,0.000009990494,0.0001106922,0.00001563767,0.00008617585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3476288,"threshold_uncertainty_score":0.5012932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01679500801497321,"score_gpt":0.216222994434994,"score_spread":0.1994279864200208,"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."}}