{"id":"W2019896551","doi":"10.1109/wcica.2014.7052759","title":"Alarm design for nonlinear stochastic systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Probability density function; Particle filter; ALARM; Nonlinear system; Monte Carlo method; Gaussian; False alarm; Algorithm; Fault detection and isolation; Function (biology); Mathematical optimization; Machine learning; Artificial intelligence; Mathematics; Engineering; Kalman filter; Statistics","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":[0.00217611,0.0008369719,0.0009223454,0.0005669365,0.0004790109,0.001094495,0.0007464493,0.001183235,0.001096041],"category_scores_gemma":[0.009160109,0.0004148103,0.0005588985,0.0002840341,0.0008077726,0.0007109288,0.00104087,0.001291304,0.0002965522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007415193,"about_ca_system_score_gemma":0.0008499625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009722108,"about_ca_topic_score_gemma":0.0005393969,"domain_scores_codex":[0.9981332,0.0006926058,0.0001298029,0.0003372862,0.0005804781,0.0001265195],"domain_scores_gemma":[0.9954084,0.002875198,0.0005536771,0.000161762,0.0008722342,0.0001287569],"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":[0.0003699321,0.00003579005,0.0007883616,0.0002230035,0.00005191247,0.0001536935,0.000165447,0.8969895,0.01130317,0.02222983,0.000983927,0.06670553],"study_design_scores_gemma":[0.00001293692,0.00006790367,0.0001364628,0.000008368818,0.000009364153,0.00003654189,0.000005482076,0.9930769,0.002266783,0.003777643,0.0005909104,0.0000107073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005789883,0.00006979086,0.9933987,0.00005909899,0.00002561336,0.00001704816,0.00001084797,0.0002308408,0.0003981311],"genre_scores_gemma":[0.8301262,0.0002158323,0.1676339,0.0001411885,0.00007428078,0.0001112721,0.00007691819,0.00006446854,0.001555896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00217611,"threshold_uncertainty_score":0.01150846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01315901531131039,"score_gpt":0.2128405345069786,"score_spread":0.1996815191956682,"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."}}