{"id":"W1543501759","doi":"10.1007/11427469_92","title":"A Dynamic Recurrent Neural Network Fault Diagnosis and Isolation Architecture for Satellite’s Actuator/Thruster Failures","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Artificial neural network; Fault detection and isolation; Fault (geology); Actuator; Real-time computing; Satellite; Architecture; Isolation (microbiology); Control theory (sociology); Control engineering; Artificial intelligence; Control (management); Engineering","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":[0.0003436876,0.0005278418,0.0005330388,0.0002170025,0.0002758185,0.0003368912,0.001240345,0.0006817793,0.002477765],"category_scores_gemma":[0.0005481772,0.0002862296,0.0003731786,0.0001388024,0.0002119674,0.0006216046,0.0004515738,0.0005852029,0.0004949867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004794266,"about_ca_system_score_gemma":0.000480781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007925184,"about_ca_topic_score_gemma":0.01180004,"domain_scores_codex":[0.9998503,0.00001756165,0.00001125384,0.0000442064,0.00005214686,0.00002448832],"domain_scores_gemma":[0.9997719,0.0000588064,0.00002616471,0.00003475439,0.00009703722,0.00001134306],"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":[0.0004025347,0.0001428853,0.0006200449,0.0001189623,0.0001030205,0.000193816,0.00008143838,0.4300587,0.05523289,0.002967358,0.003677015,0.5064014],"study_design_scores_gemma":[0.000009699605,0.00008318319,0.0002223166,0.000004091161,0.00002250029,0.00003035734,0.000003610203,0.9939486,0.004761391,0.0005298281,0.0003784301,0.0000059865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05089312,0.000534301,0.9420522,0.0001693459,0.0001156201,0.00004545446,0.00007575826,0.00335146,0.002762669],"genre_scores_gemma":[0.8651646,0.0001951287,0.1282355,0.0001231547,0.00006262716,0.00006048178,0.0001892759,0.00006968345,0.005899698],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007925184,"threshold_uncertainty_score":0.0157581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00903868970538825,"score_gpt":0.226935405256511,"score_spread":0.2178967155511227,"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."}}