{"id":"W2144892186","doi":"10.1109/icsmc.2009.5346205","title":"Diagnosis of hybrid systems: Part 2- residual generator selection and diagnosis in the presence of unreliable residual generators","year":2009,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Residual; Automaton; Hybrid system; Computer science; Generator (circuit theory); Fault (geology); Fault detection and isolation; Selection (genetic algorithm); Representation (politics); Algorithm; Artificial intelligence; Machine learning; Power (physics)","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":[0.00165392,0.0006501442,0.0006925525,0.00069732,0.0002676703,0.000979269,0.001029743,0.0008736693,0.001020942],"category_scores_gemma":[0.00341788,0.0002804151,0.0005933056,0.0004278773,0.001533805,0.001157158,0.0008083081,0.0006795336,0.0001342754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005998596,"about_ca_system_score_gemma":0.0005718016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001387801,"about_ca_topic_score_gemma":0.0006207068,"domain_scores_codex":[0.9988255,0.0003150381,0.00007565472,0.0002189163,0.0004540968,0.0001108571],"domain_scores_gemma":[0.9971938,0.002044174,0.0002223104,0.0002364973,0.0002689277,0.00003434378],"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":[0.0004025394,0.00009077743,0.005996791,0.0006243426,0.000183666,0.001681575,0.0007775939,0.684633,0.05554911,0.1005659,0.001367233,0.1481275],"study_design_scores_gemma":[0.00003422665,0.0001585105,0.001149776,0.00003724119,0.00004525491,0.0003267194,0.00007212071,0.9327937,0.02043873,0.04303137,0.001878247,0.00003401378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03737092,0.0007581407,0.960178,0.0002576275,0.00003852367,0.00003753124,0.00003754609,0.0002960578,0.001025704],"genre_scores_gemma":[0.9030688,0.0004993806,0.09473228,0.00007226513,0.0000865856,0.00007526075,0.00008455154,0.00003313076,0.001347691],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00165392,"threshold_uncertainty_score":0.008746922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009473571344771677,"score_gpt":0.2098397626656829,"score_spread":0.2003661913209112,"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."}}