{"id":"W4231480459","doi":"10.3390/wevj6030719","title":"Electric and Hybrid Vehicle Power Electronics Efficiency, Testing and Reliability","year":2013,"lang":"en","type":"article","venue":"World Electric Vehicle Journal","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Automotive engineering; Overvoltage; Reliability (semiconductor); Electric vehicle; Inverter; Power electronics; Hybrid power; Computer science; Power (physics); Hybrid vehicle; Traction (geology); Traction motor; Electronic component; Electrical engineering; Engineering; Voltage; Mechanical engineering","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":[0.0005067554,0.0002808527,0.0003012097,0.0006021986,0.0003606078,0.0002482361,0.0003362494,0.00008381756,0.0000733492],"category_scores_gemma":[0.0006149434,0.0002620773,0.00004490532,0.001928621,0.00008175876,0.0004879436,0.0001109483,0.001764679,0.00003616032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000412114,"about_ca_system_score_gemma":0.00007548808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001342757,"about_ca_topic_score_gemma":0.000003706988,"domain_scores_codex":[0.9975623,0.0000656663,0.0004335544,0.0003504013,0.0003809376,0.001207155],"domain_scores_gemma":[0.9987071,0.0004769352,0.00008332513,0.000302115,0.000183715,0.0002468272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002562452,0.0001003361,0.03595176,0.00006571418,0.00005482435,0.00006173841,0.0000462821,0.004384209,0.5192845,0.00008427577,0.003946618,0.4359941],"study_design_scores_gemma":[0.001455724,0.001044254,0.1400644,0.00006533603,0.00003686954,0.001775235,0.00003995416,0.7400219,0.09431833,0.01691423,0.003207649,0.001056203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990056,0.005409289,0.001899138,0.000519214,0.0000665465,0.0003084949,6.800032e-7,0.0004758212,0.001264854],"genre_scores_gemma":[0.9969246,0.0009067926,0.001782705,0.00007955085,0.00006465879,0.00002482318,3.073268e-7,0.00005735901,0.000159142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7356377,"threshold_uncertainty_score":0.9999831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007236461535046706,"score_gpt":0.2237662878321282,"score_spread":0.2165298262970815,"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."}}