{"id":"W3173533413","doi":"10.18280/jesa.540303","title":"Grid Voltage Estimation Based on an Adaptive Linear Neural Network for PV-Active Power Filter Control Strategy","year":2021,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Artificial neural network; Computer science; AC power; Active power filter; Control (management); Voltage; Active filter; Control engineering; Engineering; Artificial intelligence; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005845082,0.0004719274,0.0007101765,0.0001627235,0.0005940538,0.0003739787,0.0003092516,0.0002180043,0.0004269311],"category_scores_gemma":[0.0002330956,0.0003837634,0.0003741786,0.0003549115,0.00008109168,0.0006102894,0.00003290226,0.0004006311,0.00004175239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002719568,"about_ca_system_score_gemma":0.0003489619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002853114,"about_ca_topic_score_gemma":0.0003222203,"domain_scores_codex":[0.9964874,0.0008334735,0.0008948818,0.0004949748,0.0005493445,0.000739857],"domain_scores_gemma":[0.9974367,0.0004355173,0.0006723016,0.0004722292,0.000591403,0.00039183],"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":[0.0004526164,0.0001659168,0.00005769272,0.00004922986,0.0002197663,0.0004484602,0.0001361497,0.9386285,0.0007719293,0.003946565,0.003149398,0.05197379],"study_design_scores_gemma":[0.002480279,0.001749388,0.01879359,0.0003946689,0.0001023591,0.0005654338,0.0001962802,0.9662095,0.0006365455,0.001997991,0.006389091,0.0004849241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1473529,0.001705249,0.8175045,0.0004198992,0.009662281,0.001149755,0.0005737432,0.0007977095,0.02083402],"genre_scores_gemma":[0.9865451,0.00001060229,0.008747187,0.0006303765,0.001972952,0.00005615034,0.000109083,0.0001361453,0.001792426],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8391922,"threshold_uncertainty_score":0.9998614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02074717511088872,"score_gpt":0.2581056267672612,"score_spread":0.2373584516563725,"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."}}