{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00133428,0.0003758203,0.0004208951,0.0007827981,0.0001638516,0.0008162367,0.0006430522,0.0004045364,0.002730401],"category_scores_gemma":[0.002741382,0.0001648934,0.0001937373,0.0005446297,0.0004478534,0.001162051,0.0003993278,0.0002275349,0.001149163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002822073,"about_ca_system_score_gemma":0.0002123671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005620527,"about_ca_topic_score_gemma":0.0005258396,"domain_scores_codex":[0.9983717,0.0003132536,0.00007761308,0.0001154176,0.001066099,0.00005597377],"domain_scores_gemma":[0.9982785,0.0006058316,0.0001517934,0.0001985238,0.0007268009,0.00003854847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00055313,0.0002186928,0.02203641,0.0009093352,0.00006835994,0.0004630397,0.0003390992,0.04272958,0.2464966,0.01029374,0.003399447,0.6724926],"study_design_scores_gemma":[0.00006449522,0.003690429,0.08676305,0.0002608653,0.0001731711,0.003275159,0.0008843807,0.1345772,0.7008974,0.0119799,0.05730048,0.0001333862],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5316303,0.007788396,0.3963346,0.0005564502,0.0001768081,0.0002825139,0.0005258985,0.001574633,0.06113034],"genre_scores_gemma":[0.9696322,0.001471373,0.01823081,0.00005222065,0.00004476635,0.00007112852,0.0003075149,0.0001360925,0.01005393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002730401,"threshold_uncertainty_score":0.009134114,"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."}}