{"id":"W4410279045","doi":"10.1016/j.ijhydene.2025.05.013","title":"Life prediction model of automotive fuel cell based on LSTM-Transformer hybrid neural network","year":2025,"lang":"en","type":"article","venue":"International Journal of Hydrogen Energy","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Science and Technology Innovation Plan Of Shanghai Science and Technology Commission","keywords":"Automotive industry; Artificial neural network; Transformer; Computer science; Fuel cells; Automotive engineering; Artificial intelligence; Electrical engineering; Engineering; Voltage; Chemical engineering; Thermodynamics; 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":[0.0001094764,0.0004542536,0.0003456611,0.000237847,0.0002157222,0.0002904988,0.0007229858,0.0004902728,0.002055559],"category_scores_gemma":[0.0001966784,0.0001615212,0.0003402846,0.0002380223,0.0001275234,0.0005488422,0.0001858715,0.0003758703,0.0003511884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004948978,"about_ca_system_score_gemma":0.0004273362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01550196,"about_ca_topic_score_gemma":0.01192535,"domain_scores_codex":[0.9999518,0.00000430746,0.000002743456,0.00001834619,0.00001276721,0.000009962882],"domain_scores_gemma":[0.9999393,0.00001503272,0.000006014237,0.000003273166,0.00003304933,0.000003444982],"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":[0.00009157546,0.00003522981,0.001455441,0.00006516322,0.00002649941,0.0000799108,0.00002134747,0.956026,0.005964385,0.0007512601,0.001094607,0.03438857],"study_design_scores_gemma":[0.000001342473,0.000007631602,0.0001850515,0.00000127508,0.000003427821,0.000005911073,0.000001638416,0.9989428,0.0005895824,0.0001774586,0.00008226024,0.000001587923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4763584,0.002237925,0.4975363,0.0006348482,0.0003206335,0.0000709478,0.001549569,0.002539066,0.01875227],"genre_scores_gemma":[0.9918683,0.000221851,0.004609772,0.00003616231,0.00001515834,0.00003796072,0.000347515,0.00001995359,0.002843327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01550196,"threshold_uncertainty_score":0.03082347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005191561693631342,"score_gpt":0.1953205279088714,"score_spread":0.19012896621524,"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."}}