{"id":"W1772310539","doi":"10.1109/wescan.1993.270586","title":"Fault tolerant neural networks for control systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Redundancy (engineering); Fault tolerance; Computer science; Computation; Artificial neural network; Fault (geology); Artificial intelligence; Algorithm; Distributed computing","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":[0.0004377167,0.001131801,0.0007175752,0.0008810482,0.000270716,0.00106389,0.0009463239,0.00181998,0.004774991],"category_scores_gemma":[0.001483059,0.0002444779,0.0004204121,0.001601056,0.0006636003,0.001409673,0.0004860455,0.001803133,0.001848166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009389297,"about_ca_system_score_gemma":0.0004512732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002420422,"about_ca_topic_score_gemma":0.002247119,"domain_scores_codex":[0.9996291,0.00009874027,0.00002854948,0.00004978804,0.0001737351,0.00001993295],"domain_scores_gemma":[0.9997197,0.0001433355,0.00002621509,0.00002140462,0.00008147109,0.000007822869],"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":[0.00007232498,0.00006195973,0.0003369365,0.001977309,0.0001278484,0.0003304552,0.0002019077,0.1448139,0.004581729,0.3747468,0.02641852,0.4463303],"study_design_scores_gemma":[0.00003350068,0.00008715824,0.0004317471,0.0005576603,0.00006511964,0.0003259154,0.00006105313,0.3407426,0.003204306,0.3169365,0.3374981,0.00005647364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002459679,0.1001731,0.8585083,0.00373813,0.0020337,0.00008992851,0.0001895688,0.0006714167,0.03213612],"genre_scores_gemma":[0.2123747,0.2112854,0.4848852,0.003688449,0.005203811,0.0008177615,0.001077088,0.0003238187,0.08034377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004774991,"threshold_uncertainty_score":0.01597393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01019915470563769,"score_gpt":0.1930303381979648,"score_spread":0.1828311834923271,"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."}}