{"id":"W2110275585","doi":"10.4028/www.scientific.net/ast.56.247","title":"Fault Tolerant Neural Aided Controller for Multi Degree of Freedom Structures Experiencing Online Sensor Failure","year":2008,"lang":"en","type":"article","venue":"Advances in science and technology","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Controller (irrigation); Control theory (sociology); Actuator; Frame (networking); Artificial neural network; Computer science; Control engineering; Fault tolerance; Engineering; Artificial intelligence; Control (management)","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":[0.0003472147,0.000506465,0.0003005155,0.000163405,0.0002723542,0.0004201799,0.000676961,0.0005110744,0.00115818],"category_scores_gemma":[0.0007891253,0.0001349368,0.0001879185,0.0001034762,0.0003067366,0.0002401856,0.0003154604,0.0004015618,0.0001869586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003005393,"about_ca_system_score_gemma":0.0003043337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003381709,"about_ca_topic_score_gemma":0.003184021,"domain_scores_codex":[0.9998404,0.00002124058,0.00001112219,0.00004290812,0.00005873879,0.00002562735],"domain_scores_gemma":[0.9997056,0.0000811627,0.0000755709,0.00002961963,0.00009569954,0.00001228571],"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":[0.00060192,0.0001637438,0.001111439,0.0001964028,0.00004832093,0.0003542952,0.0001767139,0.8074536,0.06146644,0.002553874,0.001122115,0.1247512],"study_design_scores_gemma":[0.00002438474,0.000177458,0.0004583781,0.000004603359,0.000007418891,0.00002989121,0.000007458938,0.9932145,0.005472552,0.0002262785,0.0003725213,0.000004667279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2579734,0.0002840517,0.734746,0.0001823482,0.0001853767,0.00008122958,0.00005127553,0.001166816,0.005329473],"genre_scores_gemma":[0.990078,0.00002977122,0.008537377,0.00002339414,0.000009011052,0.00003204738,0.00001720919,0.000005833178,0.001267483],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003381709,"threshold_uncertainty_score":0.00672406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0342856673384795,"score_gpt":0.329362550835242,"score_spread":0.2950768834967625,"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."}}