{"id":"W2145152880","doi":"10.1109/63.911151","title":"Physics-based MCT circuit model using the lumped-charge modeling approach","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Power Electronics","topic":"Silicon Carbide Semiconductor Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Semtech (Canada)","funders":"","keywords":"Spice; Behavioral modeling; Thyristor; Semiconductor device; Electronic engineering; Power semiconductor device; Semiconductor device modeling; Power (physics); Electronic circuit simulation; Bipolar junction transistor; Physics; Transistor; Computer science; Voltage; Electrical engineering; Engineering; CMOS; Electronic circuit; Materials science","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":[0.0001311079,0.0003432462,0.000247434,0.0001542202,0.0002325898,0.00006165081,0.0004208556,0.0002231238,0.00003277784],"category_scores_gemma":[0.000003413583,0.0003143874,0.0002079671,0.0005357226,0.00006527804,0.0002220356,0.000001391826,0.001009427,0.00001890678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004854578,"about_ca_system_score_gemma":0.000121654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001168718,"about_ca_topic_score_gemma":0.000008329087,"domain_scores_codex":[0.9983652,0.00002359602,0.0002773517,0.0003496118,0.000281079,0.0007031463],"domain_scores_gemma":[0.9990791,0.00004544236,0.0000265386,0.0007337758,0.00005852056,0.00005659805],"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":[0.000007872247,0.00005895162,8.810595e-7,0.000009482758,0.00005888902,0.000001019992,0.0001177636,0.8405032,0.1577528,0.0001973604,0.00002084134,0.001270893],"study_design_scores_gemma":[0.0002663179,0.00003158502,9.709422e-8,0.00001096196,0.00005652319,0.00001753396,0.00008026611,0.8732625,0.1250972,0.0008197471,0.00005784218,0.0002994368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3419777,0.0004031135,0.6556633,0.00002736337,0.0002128958,0.0002052882,0.00001256611,0.0009396738,0.0005581472],"genre_scores_gemma":[0.9987397,0.000193889,0.0006711442,0.0001246801,0.00002654397,0.00006351218,0.00000305021,0.0001205893,0.00005688601],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6567621,"threshold_uncertainty_score":0.9999308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04065096285878852,"score_gpt":0.2410679257235578,"score_spread":0.2004169628647693,"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."}}