{"id":"W4287595676","doi":"10.1109/isie51582.2022.9831502","title":"Loss Comparison of Electric Vehicle Fuel Cell Integration Methods","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Drivetrain; Inverter; Dual (grammatical number); Automotive engineering; Harmonics; Driving cycle; Voltage source inverter; Voltage; Electric vehicle; Computer science; Power (physics); Engineering; Electrical engineering; Torque; 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":[0.0009169945,0.0005117548,0.0005283054,0.001931545,0.0003261456,0.0009332165,0.001244067,0.0003543169,0.001994214],"category_scores_gemma":[0.002109708,0.0002778836,0.0003396829,0.001094409,0.0002674986,0.001292845,0.0005947463,0.0003354761,0.000627536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008579056,"about_ca_system_score_gemma":0.0002703948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001447412,"about_ca_topic_score_gemma":0.001742724,"domain_scores_codex":[0.9986839,0.00010288,0.00003805397,0.00009788389,0.0009791984,0.0000980587],"domain_scores_gemma":[0.9990747,0.0002335254,0.00006721101,0.00009230733,0.0005051235,0.00002713823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004005781,0.0007638801,0.02821305,0.001050869,0.0002803763,0.0003881514,0.0004792085,0.1075855,0.1161356,0.004865867,0.0034174,0.7328144],"study_design_scores_gemma":[0.0001859853,0.003796914,0.06231751,0.0001693315,0.0003475378,0.001168373,0.0007266051,0.4871542,0.4170557,0.001843821,0.02509793,0.0001360766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.846981,0.00368644,0.1332742,0.0001433429,0.0001381822,0.0001462331,0.0003372885,0.0009254334,0.01436776],"genre_scores_gemma":[0.9736201,0.0008215698,0.01970572,0.00002658522,0.00001853904,0.00006885883,0.0004150781,0.0001127789,0.005210744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001994214,"threshold_uncertainty_score":0.006671309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02574692428326547,"score_gpt":0.2918162822024525,"score_spread":0.266069357919187,"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."}}