{"id":"W2547429387","doi":"10.1109/epe.2016.7695301","title":"Efficient intelligent control techniques for DC-DC converters: A comparative study","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Converters; MATLAB; Computer science; Fuzzy logic; Control engineering; Transient (computer programming); Fuzzy control system; Electronic engineering; Intelligent control; Control theory (sociology); Control system; Voltage; Engineering; Control (management); Artificial intelligence; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001302385,0.00023841,0.0003478552,0.0001013808,0.0000418231,0.00001904251,0.0001854153,0.00004865032,0.0001190654],"category_scores_gemma":[0.00002111185,0.0001596254,0.00008806554,0.00008519689,0.00005763075,0.00006705723,0.00002730863,0.00006390989,0.0001118602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001817379,"about_ca_system_score_gemma":0.0000107921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005853724,"about_ca_topic_score_gemma":0.00001933842,"domain_scores_codex":[0.9989203,0.00002528371,0.0003091091,0.0002685762,0.0001447755,0.0003319878],"domain_scores_gemma":[0.9991893,0.0002918578,0.00003557043,0.0002958768,0.00009009405,0.00009734539],"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":[0.0004862707,0.000937607,0.001645422,0.0001120084,0.001005863,0.00001780765,0.006524369,0.002573907,0.07546326,0.002883952,0.006291027,0.9020585],"study_design_scores_gemma":[0.004850832,0.001179143,0.0003379464,0.000115518,0.0001014303,0.000006114142,0.004055861,0.8773742,0.09880066,0.0003630277,0.01190601,0.0009093086],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02509959,0.00004728787,0.970879,0.0001014743,0.000264157,0.002015504,0.0000227954,0.0009126625,0.0006575885],"genre_scores_gemma":[0.995985,0.000004769882,0.002990621,0.000109285,0.00004707175,0.0005265932,0.000001279627,0.0000359281,0.0002995012],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9708853,"threshold_uncertainty_score":0.6509336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02152075160699433,"score_gpt":0.279838827252048,"score_spread":0.2583180756450537,"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."}}