{"id":"W2104197126","doi":"10.1109/icsmc.1995.538037","title":"Techniques for confident and reliable fault detection in large scale engineering plants","year":2002,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Fault detection and isolation; Scale (ratio); Domain (mathematical analysis); Fault (geology); Algorithm; Artificial intelligence; Mathematics; Actuator","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":[0.00005427896,0.00003768875,0.00004413719,0.00003208579,0.00003678624,0.00003977107,0.00008333394,0.00002260444,0.000003615424],"category_scores_gemma":[0.000001937048,0.00003396172,0.000008766962,0.00007896968,0.000002763349,0.0001145815,0.00003189396,0.00003538862,0.000002371859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007445942,"about_ca_system_score_gemma":7.284928e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001465057,"about_ca_topic_score_gemma":0.00005061209,"domain_scores_codex":[0.9996638,0.000001705279,0.00007005855,0.0001225793,0.00003264044,0.0001091915],"domain_scores_gemma":[0.9998428,0.00002128504,0.00001146985,0.000093496,0.00000841917,0.0000225576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000120307,0.0004611203,0.002306174,0.0001244355,0.00001661649,0.000009089097,0.001560268,0.003167466,0.134974,0.09539451,0.01873583,0.7432384],"study_design_scores_gemma":[0.0001022003,0.00002220776,0.0003813766,0.00001002104,4.353166e-7,0.000005655428,0.000007205084,0.9304739,0.05019016,0.0003699479,0.01837587,0.00006099328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04253179,0.00005833841,0.9562938,0.0002791128,0.00003354092,0.0002147811,0.000001151568,0.0001496513,0.0004378015],"genre_scores_gemma":[0.9688188,0.00006083083,0.03062726,0.00009676579,0.00002231563,0.00008849241,3.492034e-7,0.000002811606,0.0002823869],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9273065,"threshold_uncertainty_score":0.1384919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049403490661148,"score_gpt":0.2209577898239001,"score_spread":0.2104637549172887,"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."}}