{"id":"W4200117312","doi":"10.3390/app112411796","title":"Online Monitoring of Power Converter Degradation Using Deep Neural Network","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Silicon Carbide Semiconductor Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Korea Institute of Radiological and Medical Sciences","keywords":"Snubber; Insulated-gate bipolar transistor; Computer science; Spectrogram; Resistor; Grayscale; Convolutional neural network; Waveform; Converters; Voltage; Electronic engineering; Artificial intelligence; Electrical engineering; Engineering; Capacitor; Image (mathematics)","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":[0.00009047371,0.00008967631,0.0001304773,0.00005390226,0.00005775817,0.00002913165,0.0001946916,0.00005783571,0.00002326987],"category_scores_gemma":[0.00002131271,0.00008614108,0.00002641755,0.0005386383,0.0001598049,0.0001207096,0.00005120338,0.00009498459,0.000002189236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002656696,"about_ca_system_score_gemma":0.00001798373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005144604,"about_ca_topic_score_gemma":0.000005427029,"domain_scores_codex":[0.9992877,0.000006380568,0.0001662519,0.0001645466,0.0001648452,0.0002102679],"domain_scores_gemma":[0.9997054,0.00005435613,0.00003426843,0.0001547619,0.00003005854,0.00002111582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[6.732106e-7,0.000007413817,0.01280263,0.000009588461,0.00001023187,0.000002001774,0.00008896545,0.06890869,0.911583,0.0008062259,0.00002207732,0.005758484],"study_design_scores_gemma":[0.0001301201,0.00001315005,0.008607477,0.0000222871,0.00001273511,0.00001137271,0.002744311,0.2279932,0.7594461,0.0007770919,0.0000413825,0.000200775],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971735,0.0007927031,0.0005291488,0.00001784973,0.0006339725,0.00004726783,0.000001436098,0.0002092046,0.0005948555],"genre_scores_gemma":[0.9928698,0.00001529772,0.00701808,0.00001679649,0.00006349126,0.000002425344,0.000001679097,0.000009005079,0.000003402446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1590845,"threshold_uncertainty_score":0.3512731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03801575006552831,"score_gpt":0.2619042129776043,"score_spread":0.223888462912076,"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."}}