{"id":"W4308993051","doi":"10.1109/globconpt57482.2022.9938236","title":"International Speaker","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Victoria","funders":"","keywords":"Power electronics; Electronics; Renewable energy; Converters; Electrical engineering; Power module; Power semiconductor device; Power (physics); Computer science; Electric power; Energy transformation; Engineering; Voltage","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":[0.000183852,0.0002650059,0.0002401746,0.0001280585,0.0003657681,0.0001000956,0.00159447,0.00009994749,0.0004249132],"category_scores_gemma":[0.00004674167,0.0003030823,0.00005690243,0.0003787289,0.0002197898,0.0001354148,0.001121071,0.0006641955,0.00004337889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003870064,"about_ca_system_score_gemma":0.0000288657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001822398,"about_ca_topic_score_gemma":0.000009946871,"domain_scores_codex":[0.9985784,0.0000713527,0.0003348062,0.0003507949,0.000338892,0.0003258058],"domain_scores_gemma":[0.9986845,0.00006506716,0.0001148225,0.001012082,0.00007516847,0.0000483222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005825887,0.0001420722,0.002120018,0.00001997248,0.0001871859,0.00002106211,0.0004771839,0.003239553,0.0009342657,0.1488441,0.02026803,0.8236883],"study_design_scores_gemma":[0.00213197,0.000588104,0.004369864,0.0001103774,0.00004394747,0.000226884,0.01350665,0.5491673,0.0008773646,0.03837287,0.3888619,0.001742776],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3088877,0.006512917,0.2429248,0.01444396,0.007609796,0.001764725,0.0006285613,0.01801416,0.3992134],"genre_scores_gemma":[0.9970769,0.0008179914,0.00162482,0.0002655326,0.00001102838,0.00004428237,0.00004089837,0.00001995088,0.0000986297],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8219455,"threshold_uncertainty_score":0.9999421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01265785581259354,"score_gpt":0.2469878330152464,"score_spread":0.2343299772026529,"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."}}