{"id":"W4313563309","doi":"10.1109/vppc55846.2022.10003313","title":"Fuel Cell Ageing Prediction and Remaining Useful Life Forecasting","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Vehicle Power and Propulsion Conference (VPPC)","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Université du Québec à Trois-Rivières","funders":"","keywords":"Benchmark (surveying); Long short term memory; Computer science; Generalization; Mean squared error; Estimation; Term (time); Reliability engineering; Degradation (telecommunications); Artificial neural network; Machine learning; Artificial intelligence; Engineering; Statistics; Recurrent neural network; Mathematics; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003839698,0.0002082729,0.0002438767,0.0001136896,0.0004242604,0.0001325863,0.0001079216,0.0001009467,0.0006977122],"category_scores_gemma":[0.00002111745,0.0001992481,0.00003708239,0.0001689013,0.00004297469,0.0001856808,0.0001492134,0.0004173101,0.000007279983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000344051,"about_ca_system_score_gemma":0.00002897425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002539817,"about_ca_topic_score_gemma":0.000003000535,"domain_scores_codex":[0.9986805,0.00008695704,0.0003303128,0.00033162,0.000242309,0.0003283363],"domain_scores_gemma":[0.9995164,0.00005348646,0.00007206762,0.0001603114,0.00003479021,0.0001629356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006947718,0.0003348874,0.01400264,0.008230681,0.0003452204,0.00065963,0.03038965,0.07973332,0.817484,0.0002636978,0.01117961,0.03668187],"study_design_scores_gemma":[0.003860278,0.001182466,0.004145319,0.0003574915,0.0001701471,0.0002261037,0.005467366,0.9089908,0.01959303,0.001917127,0.05249095,0.001598957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825394,0.0037583,0.0001531111,0.0001044442,0.001663275,0.0002834882,0.0000599499,0.0002537182,0.01118433],"genre_scores_gemma":[0.9976244,0.001610441,0.0001843918,0.00007133089,0.00008881171,0.00004675092,0.00001942327,0.00004434354,0.0003100896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8292574,"threshold_uncertainty_score":0.81251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01882331218797027,"score_gpt":0.1907942363713435,"score_spread":0.1719709241833733,"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."}}