{"id":"W3112727022","doi":"10.1109/smc42975.2020.9283435","title":"Use of A Data-Driven Approach for Time Series Prediction in Fault Prognosis of Satellite Reaction Wheel","year":2020,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Autoregressive integrated moving average; Satellite; Computer science; Autoregressive model; Time series; Recurrent neural network; Series (stratigraphy); Fault (geology); Process (computing); Artificial neural network; Data mining; Real-time computing; Artificial intelligence; Machine learning; Engineering; Statistics; Mathematics","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":[0.0007775312,0.0007190477,0.0005830814,0.0009952224,0.0002623731,0.0007175855,0.0007070974,0.0008292924,0.0006976503],"category_scores_gemma":[0.002713416,0.0003002875,0.0006258839,0.0007697447,0.0001703023,0.0006770045,0.0002961369,0.001019608,0.000234508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006217388,"about_ca_system_score_gemma":0.0006270368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01641713,"about_ca_topic_score_gemma":0.01312514,"domain_scores_codex":[0.9997863,0.00004308104,0.00002632356,0.00007404315,0.00004506423,0.0000251256],"domain_scores_gemma":[0.9990852,0.0004457347,0.0001101689,0.0000581522,0.0002607528,0.00004005006],"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":[0.00009450111,0.0001196645,0.005713952,0.00007169157,0.00008559247,0.0001464198,0.00004034609,0.9399976,0.002479711,0.0009917199,0.0008872264,0.04937157],"study_design_scores_gemma":[0.000001294405,0.000007792968,0.0004782737,0.000002587056,0.000003789953,0.000005133712,0.000003084373,0.9988213,0.0003331014,0.0002621174,0.00007786627,0.000003617109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3824391,0.001078626,0.6084886,0.0009432663,0.0003368483,0.0001015823,0.002282278,0.002013756,0.002315956],"genre_scores_gemma":[0.9670962,0.0002261421,0.03035149,0.00006510682,0.00005085848,0.00006284449,0.001433102,0.00002932871,0.0006849042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01641713,"threshold_uncertainty_score":0.0326432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04507293354979217,"score_gpt":0.2308869313498733,"score_spread":0.1858139978000811,"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."}}