{"id":"W2015589096","doi":"10.1002/prs.11609","title":"Dynamic risk assessment and fault detection using a multivariate technique","year":2013,"lang":"en","type":"article","venue":"Process Safety Progress","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Fault detection and isolation; Context (archaeology); Process (computing); Kalman filter; Residual; Multivariate statistics; Fault (geology); Reliability engineering; Computer science; Engineering; Multivariable calculus; Risk analysis (engineering); Data mining; Artificial intelligence; Machine learning; Algorithm; Control engineering; Medicine","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":[0.001163292,0.0009214367,0.0008686093,0.001922404,0.0002937764,0.0008826744,0.0007223309,0.0006403581,0.001404976],"category_scores_gemma":[0.005176662,0.0003035328,0.0008342285,0.001060979,0.0005913659,0.001278681,0.001180025,0.001171617,0.0002922916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005316614,"about_ca_system_score_gemma":0.0006707736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0020964,"about_ca_topic_score_gemma":0.001708442,"domain_scores_codex":[0.9988202,0.00030781,0.00006314865,0.0002336472,0.0004930883,0.00008209678],"domain_scores_gemma":[0.9980286,0.0009249658,0.0004231356,0.0002197758,0.0003414277,0.00006206279],"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":[0.0002555675,0.0001487456,0.008016056,0.0001788866,0.0001661731,0.0002535276,0.0002350929,0.4719449,0.0346476,0.02863585,0.001079001,0.4544386],"study_design_scores_gemma":[0.000009841496,0.0001117729,0.00260016,0.00001155665,0.00003336372,0.0001930081,0.00002913259,0.9756231,0.008076517,0.01182542,0.001439054,0.0000470133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007779299,0.00008906239,0.9914976,0.00005762553,0.00000972609,0.00001063936,0.00001743365,0.0001790854,0.0003595672],"genre_scores_gemma":[0.6792072,0.0003549121,0.3182601,0.00005611584,0.00008876518,0.00006041016,0.0001049698,0.00008593338,0.00178152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0020964,"threshold_uncertainty_score":0.006152153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005946731101251014,"score_gpt":0.2692157046531937,"score_spread":0.2632689735519427,"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."}}