{"id":"W1941258674","doi":"10.1109/intlec.1996.573414","title":"Thermal analysis and optimization of a small, high density DC power system by finite element analysis (FEA)","year":2002,"lang":"en","type":"article","venue":"","topic":"Silicon Carbide Semiconductor Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Finite element method; Modular design; Convection; Thermal conduction; Heat transfer; Heat transfer coefficient; Convective heat transfer; Thermal; Natural convection; Mechanical engineering; Thermal analysis; Power (physics); Power density; Mechanics; Materials science; Engineering; Computer science; Thermodynamics; Structural engineering; Physics; Composite material","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":[],"consensus_categories":[],"category_scores_codex":[0.00009344499,0.0001564981,0.0004060168,0.0005451633,0.00002518763,0.00002639534,0.0001348256,0.0001200483,0.0004475591],"category_scores_gemma":[0.00002435961,0.0001438313,0.0001423938,0.001549416,0.00003875324,0.0000813493,0.00004844005,0.00007759361,0.000003743984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006959059,"about_ca_system_score_gemma":0.000001438505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001929365,"about_ca_topic_score_gemma":0.00007824048,"domain_scores_codex":[0.999153,0.00002249712,0.0002990951,0.000211917,0.0001387179,0.0001748216],"domain_scores_gemma":[0.9993935,0.00006030806,0.00006654391,0.0003802477,0.00006035542,0.00003899982],"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":[0.000001712256,0.00001438503,0.01922829,0.00002814503,0.003407354,0.000001932983,0.0000871484,0.93955,0.03716161,0.00007989321,0.0001416487,0.0002978363],"study_design_scores_gemma":[0.0001447312,0.00001733209,0.004188559,0.000004029939,0.001729168,4.163429e-7,0.0003173696,0.9176278,0.07581282,9.39069e-7,0.000006105491,0.0001507642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9283008,0.0003963779,0.07011589,0.0000263794,0.00003169533,0.00009189812,0.00002533955,0.0005340786,0.0004775341],"genre_scores_gemma":[0.9960514,0.00006941456,0.003747506,0.00001222796,0.000004388947,0.00000812836,0.00002178645,0.00001464004,0.00007053903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06775056,"threshold_uncertainty_score":0.5865272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009156184698584235,"score_gpt":0.1788224637919664,"score_spread":0.1696662790933822,"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."}}