{"id":"W2014544957","doi":"10.1109/tvt.2011.2177483","title":"Two-Stage Energy Management Control of Fuel Cell Plug-In Hybrid Electric Vehicles Considering Fuel Cell Longevity","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Proton exchange membrane fuel cell; Energy management; Controller (irrigation); Automotive engineering; Engineering; Battery (electricity); Model predictive control; Electric vehicle; Fuel efficiency; Control theory (sociology); Computer science; Energy (signal processing); Fuel cells; Control (management)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001469589,0.0003762925,0.0005058157,0.001837736,0.00006476969,0.0000106494,0.0006343221,0.0003337716,0.00008425012],"category_scores_gemma":[0.000005344345,0.0004223238,0.0001422548,0.001139509,0.0002439601,0.0001431025,0.00001351582,0.0009113421,0.00003699659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002624469,"about_ca_system_score_gemma":0.00002305312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006331872,"about_ca_topic_score_gemma":0.0001228509,"domain_scores_codex":[0.9978634,0.00004523281,0.0005260043,0.0005132674,0.000268299,0.0007837953],"domain_scores_gemma":[0.9987795,0.00009171703,0.00008531597,0.0009148137,0.00006142983,0.00006716128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000283009,0.001535563,0.000841819,0.002216632,0.0004585555,0.001797143,0.0001086354,0.5853338,0.2927813,0.001879073,0.00004425954,0.1127202],"study_design_scores_gemma":[0.002146436,0.0002175908,0.00009547557,0.00005004684,0.00004933279,0.00002794349,0.0001460603,0.04276642,0.9508358,0.002367405,0.0008807949,0.000416666],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2551638,0.00193994,0.738061,0.00005051889,0.0001610046,0.0004619631,0.00003288034,0.001372293,0.00275658],"genre_scores_gemma":[0.9912388,0.00212049,0.006142725,0.00002917246,0.000005546299,0.0002689793,0.000001424385,0.00008381222,0.0001091007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7360749,"threshold_uncertainty_score":0.9998229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01194718591237605,"score_gpt":0.215218269338707,"score_spread":0.203271083426331,"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."}}