{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001960067,0.00008482818,0.0001318513,0.00003828307,0.00003314218,0.00003885363,0.00006122592,0.0000515006,0.00001103794],"category_scores_gemma":[0.00003295042,0.00007323773,0.00004058668,0.00004575561,0.000004700662,0.00003322643,0.000002703365,0.00003810804,0.0001225871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002159263,"about_ca_system_score_gemma":0.000003634126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001208187,"about_ca_topic_score_gemma":0.000003835189,"domain_scores_codex":[0.9995311,0.00001876759,0.0001439741,0.00008612545,0.00006764691,0.0001523206],"domain_scores_gemma":[0.9996724,0.0001127225,0.00001172649,0.0001223372,0.00002637104,0.00005450592],"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":[0.00001088748,0.00000617499,9.51957e-7,0.00008001411,0.00003570252,1.429317e-7,0.00002888304,0.9872643,0.003761384,0.001308516,0.004635432,0.002867569],"study_design_scores_gemma":[0.0004063548,0.00004952848,0.00000250947,0.00001094591,0.000007439249,0.00000488609,0.0000360404,0.9563992,0.0003066144,0.0000220455,0.04265813,0.00009629381],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009102506,0.00009389574,0.9941746,0.00001565702,0.00121112,0.0004152682,0.000003485342,0.0005374874,0.002638229],"genre_scores_gemma":[0.9963759,6.431954e-7,0.001666722,0.00002622328,0.0003720565,0.0001706719,0.000002086303,0.00002771901,0.001358031],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9954656,"threshold_uncertainty_score":0.2986548,"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."}}