{"id":"W3158285820","doi":"10.18280/mmep.080208","title":"A Dual Frequency Compensation Technique to Improve Stability and Transient Response for a Three Stage Low-Drop-Out Linear Regulator","year":2021,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Low-dropout regulator; Dropout voltage; Line regulation; Voltage regulator; Control theory (sociology); Transient response; Frequency compensation; Linear regulator; Regulator; Capacitor; Voltage; Load regulation; Compensation (psychology); Transient (computer programming); Voltage divider; Physics; Engineering; Electrical engineering; Computer science","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":[0.0002693936,0.000437055,0.0004584468,0.0004208798,0.0004232633,0.0006562093,0.0009464528,0.0007159942,0.001778759],"category_scores_gemma":[0.0005450194,0.0002307151,0.0003529473,0.0003455049,0.000264673,0.0005299452,0.0003589161,0.000618904,0.0004693228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004792218,"about_ca_system_score_gemma":0.0004402357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006339937,"about_ca_topic_score_gemma":0.001143224,"domain_scores_codex":[0.9996226,0.00004250113,0.00002020544,0.00008081959,0.0001828658,0.00005088199],"domain_scores_gemma":[0.9997045,0.00007365482,0.00005965302,0.00002964263,0.0001192298,0.00001322513],"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":[0.0001839508,0.00004587032,0.0006363326,0.000146268,0.00002926373,0.0001402053,0.0001499446,0.006220005,0.8997409,0.003763668,0.0009169928,0.08802659],"study_design_scores_gemma":[0.00007379625,0.0006828876,0.001391881,0.00003493236,0.00009430192,0.001097055,0.00004914709,0.2911198,0.6866378,0.00114497,0.01759865,0.00007481797],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06452494,0.0005849726,0.9295118,0.0002661553,0.0001377373,0.00005610932,0.00003444652,0.001387086,0.003496711],"genre_scores_gemma":[0.8760221,0.0002572597,0.117933,0.0002079172,0.00009350549,0.00004830264,0.00005864955,0.00008230469,0.005297116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001778759,"threshold_uncertainty_score":0.005950511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02997674258365702,"score_gpt":0.2181940443229273,"score_spread":0.1882173017392703,"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."}}