{"id":"W2102236750","doi":"10.1109/isie.2008.4677252","title":"An improved powertrain topology for fuel cell-battery-ultracapacitor vehicles","year":2008,"lang":"en","type":"article","venue":"","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Powertrain; Battery (electricity); Network topology; Supercapacitor; Topology (electrical circuits); Automotive engineering; Fuel cells; Energy storage; Computer science; Electric vehicle; Engineering; Electrical engineering; Power (physics); Capacitance; Torque; Computer network","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":[0.00009158924,0.0003454662,0.0002249715,0.0003124251,0.0003295672,0.0004355112,0.0006286516,0.0002517459,0.003379303],"category_scores_gemma":[0.0002110392,0.0001050812,0.0002105566,0.0004424639,0.0001306291,0.001306902,0.0003236317,0.0004355832,0.0005659612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001938141,"about_ca_system_score_gemma":0.0001544888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008085269,"about_ca_topic_score_gemma":0.001407184,"domain_scores_codex":[0.9999355,0.0000105352,0.000005530334,0.000009287666,0.00003197442,0.000007256077],"domain_scores_gemma":[0.9999235,0.00001099915,0.00000584068,0.000009643641,0.00004189039,0.000008204693],"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":[0.0004017856,0.0002726694,0.001473207,0.000569601,0.00007525595,0.001256357,0.0002332866,0.4062172,0.07435356,0.1040119,0.02012228,0.3910129],"study_design_scores_gemma":[0.0001738137,0.000564806,0.001481135,0.00005841502,0.00007442047,0.001532065,0.0001741522,0.8228002,0.03311584,0.035793,0.104158,0.0000741954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.171132,0.00186926,0.7648947,0.0007190369,0.0008799312,0.0002012275,0.0007625235,0.0015724,0.05796903],"genre_scores_gemma":[0.8715945,0.001186646,0.1122439,0.00008739815,0.0001285921,0.0001371643,0.0008498296,0.00009053031,0.01368157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003379303,"threshold_uncertainty_score":0.01130491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01055827226685454,"score_gpt":0.2124629975582163,"score_spread":0.2019047252913617,"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."}}