{"id":"W2899383815","doi":"","title":"Performance of Wide Band Gap Devices in Electric Vehicles Converters: A Case Study Evaluation","year":2018,"lang":"en","type":"article","venue":"European Conference on Power Electronics and Applications","topic":"Silicon Carbide Semiconductor Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Converters; Silicon carbide; Gallium nitride; Wide-bandgap semiconductor; Work (physics); Battery (electricity); Electronic engineering; Electric vehicle; Materials science; Computer science; Electrical engineering; Automotive engineering; Engineering; Optoelectronics; Voltage; Power (physics); Mechanical engineering; Physics; Nanotechnology","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":[0.0004140131,0.0003923044,0.0004436718,0.0003852059,0.000258836,0.0008293216,0.0006272194,0.000594374,0.001745719],"category_scores_gemma":[0.0006276207,0.0001166134,0.0003829163,0.0003550799,0.0002355184,0.0005951353,0.0002116751,0.0002448633,0.0002970188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000696445,"about_ca_system_score_gemma":0.0002008735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001811957,"about_ca_topic_score_gemma":0.002073231,"domain_scores_codex":[0.9997241,0.00005702794,0.000008995163,0.00003609624,0.0001249563,0.00004898954],"domain_scores_gemma":[0.9996475,0.0001552967,0.00002865147,0.00003471254,0.0001180684,0.00001574895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001451169,0.0008777824,0.01861392,0.0009853054,0.000193211,0.001768211,0.0003832888,0.7921382,0.09957965,0.004104682,0.00239397,0.0775107],"study_design_scores_gemma":[0.00009773865,0.004537349,0.01687936,0.00009641957,0.0001819143,0.001047686,0.0008126015,0.7411594,0.2245503,0.001387282,0.009197003,0.00005292434],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864528,0.0005710807,0.004222271,0.00007252636,0.00001717975,0.00003938717,0.0001417693,0.00009580924,0.008387226],"genre_scores_gemma":[0.9982962,0.0001271959,0.0005471426,0.000004643479,0.000001868992,0.000007216338,0.00003495203,0.000006674715,0.0009740343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001811957,"threshold_uncertainty_score":0.005840063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03105744352653945,"score_gpt":0.2687726365018586,"score_spread":0.2377151929753191,"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."}}