{"id":"W2023146858","doi":"10.5539/mas.v1n4p87","title":"Modeling the Bi-directional DC-DC Converter for HEV's","year":2007,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Converters; Transformer; Forward converter; Electronic circuit; Inductor; Ordinary differential equation; DC bias; State variable; Differential equation; Computer science; Mathematics; Boost converter; Physics; Voltage; Engineering; Electrical engineering; Mathematical analysis; Control (management)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001477879,0.0003586645,0.0003521219,0.0002300099,0.0003265892,0.0007439995,0.0007061195,0.000536395,0.002078618],"category_scores_gemma":[0.0002392966,0.0001937426,0.0003306797,0.0002495928,0.0002707062,0.0008085754,0.0002857216,0.0006216792,0.0005682172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005123624,"about_ca_system_score_gemma":0.0006397183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004011,"about_ca_topic_score_gemma":0.003610297,"domain_scores_codex":[0.9998584,0.00002813455,0.000006633325,0.00003614611,0.00006065117,0.000009934438],"domain_scores_gemma":[0.9999504,0.0000121703,0.000005270822,0.000008049064,0.00002137174,0.000002834447],"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":[0.000057601,0.00004567957,0.0008033182,0.0001477115,0.00003562169,0.000134414,0.00008818042,0.8924338,0.0213425,0.04181103,0.001255188,0.04184488],"study_design_scores_gemma":[0.000006917508,0.00002946223,0.0002219632,0.000006117092,0.000009904771,0.00005162688,0.00001462399,0.987554,0.002442631,0.004571228,0.005085344,0.000006250484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03192514,0.0007847401,0.9472941,0.0002576296,0.0001094228,0.00009257444,0.0001772107,0.0005444587,0.01881478],"genre_scores_gemma":[0.9100897,0.001702709,0.06425153,0.00008628304,0.00005500098,0.0002052507,0.0002283988,0.00005840737,0.02332267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004011,"threshold_uncertainty_score":0.00797534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01685925890421202,"score_gpt":0.2388326634457884,"score_spread":0.2219734045415763,"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."}}