{"id":"W2958658808","doi":"10.1002/stc.2404","title":"Real‐time anomaly detection with Bayesian dynamic linear models","year":2019,"lang":"en","type":"article","venue":"Structural Control and Health Monitoring","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Hydro-Québec","keywords":"Anomaly detection; Bayesian probability; Anomaly (physics); Computer science; Artificial intelligence; Pattern recognition (psychology); Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0017449,0.0008816982,0.001069109,0.0009960543,0.000287016,0.001070861,0.001420825,0.001280149,0.0009631325],"category_scores_gemma":[0.006959342,0.0009580699,0.0008028873,0.001073792,0.0007099803,0.001615614,0.001054655,0.002360123,0.0004759841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009775152,"about_ca_system_score_gemma":0.001152327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01066063,"about_ca_topic_score_gemma":0.007723181,"domain_scores_codex":[0.9987929,0.0004137686,0.00006039675,0.0003164158,0.0003224803,0.00009414214],"domain_scores_gemma":[0.9972761,0.001851473,0.0003699831,0.0001431966,0.0003049421,0.00005426471],"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":[0.0001035931,0.00007006624,0.001124856,0.0000812878,0.000090371,0.00006145869,0.0000835654,0.861478,0.002346556,0.01264999,0.00134427,0.1205661],"study_design_scores_gemma":[0.00000342695,0.000008201891,0.0001193109,0.000002922372,0.000002938842,0.000009114208,0.00000262259,0.9960061,0.0002425719,0.003320927,0.0002764004,0.000005495546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003987872,0.0002013246,0.9949331,0.0001287417,0.00001878341,0.000009216393,0.00003405345,0.0003936334,0.0002933737],"genre_scores_gemma":[0.6030001,0.000928124,0.389708,0.0002469978,0.0001692207,0.0002201221,0.0005909592,0.0001822714,0.004954151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01066063,"threshold_uncertainty_score":0.02119714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00942687170045171,"score_gpt":0.2725016903912342,"score_spread":0.2630748186907825,"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."}}