{"id":"W2141421654","doi":"10.1109/tpwrd.2004.835036","title":"Mitigation of Voltage Disturbances Using Adaptive Perceptron-Based Control Algorithm","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Voltage; Harmonics; Control theory (sociology); Disturbance voltage; Voltage sag; Engineering; Fault (geology); Algorithm; Computer science; Voltage regulation; Electronic engineering; Voltage optimisation; Control (management); Power quality; Electrical engineering; Artificial intelligence","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":[0.0001061637,0.0001829813,0.000224259,0.0001370517,0.00009479163,0.00001685877,0.0001063276,0.0001087221,0.0002156218],"category_scores_gemma":[0.000001211897,0.0002001031,0.0001666728,0.0001489039,0.00008445983,0.0002632244,2.546341e-7,0.0002338794,0.00003511478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001734419,"about_ca_system_score_gemma":0.00004315799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003762281,"about_ca_topic_score_gemma":0.00003102162,"domain_scores_codex":[0.999045,0.00003602834,0.0002989348,0.0001719545,0.0002243536,0.000223713],"domain_scores_gemma":[0.9995114,0.0001022041,0.00004725595,0.0001912327,0.00007427968,0.00007365498],"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":[0.00007776279,0.0001869325,0.000006343077,0.00002947233,0.0001429657,0.000002935391,0.0007272467,0.9486974,0.02645838,0.00002189042,0.0001380116,0.02351061],"study_design_scores_gemma":[0.0009967494,0.0001177477,0.0001647266,0.00006816944,0.00009721839,0.000002414679,0.0002179433,0.8977553,0.09937083,0.00001900746,0.0009182546,0.0002716454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1234882,0.0002796494,0.8748587,0.00003046324,0.0004476622,0.0001491542,0.000308391,0.00014889,0.00028895],"genre_scores_gemma":[0.9945592,0.00003889157,0.005142775,0.0001343634,0.00003578538,0.00001289414,0.000004021338,0.00002958332,0.00004249479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.871071,"threshold_uncertainty_score":0.8159965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554959600233699,"score_gpt":0.2230044728660893,"score_spread":0.2074548768637523,"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."}}