{"id":"W2901902180","doi":"10.1109/tpel.2018.2881164","title":"Harmonic Compensation Optimization for Multiple Parallel Distributed Generators","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Power Electronics","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Comunidad de Madrid","keywords":"Harmonic; Compensation (psychology); Voltage source; Voltage; Control theory (sociology); Computer science; Electronic engineering; Topology (electrical circuits); Engineering; Electrical engineering; Control (management); Physics","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":[0.00007941415,0.0001930081,0.000154277,0.000104717,0.0002285123,0.00005380763,0.0001031403,0.0001262199,0.0001425018],"category_scores_gemma":[0.000004431554,0.0002101435,0.00009822878,0.000247459,0.00003165118,0.0001609488,3.90837e-7,0.0001544434,0.00002769208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002210599,"about_ca_system_score_gemma":0.00004459744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002601443,"about_ca_topic_score_gemma":0.00006253779,"domain_scores_codex":[0.9990376,0.00001991436,0.0002463227,0.0002131399,0.0001102036,0.0003728479],"domain_scores_gemma":[0.999496,0.00004788391,0.00003896736,0.0001989945,0.0001521114,0.00006601856],"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":[0.00008070531,0.00005252218,0.000002068182,0.000008013115,0.00006894425,1.405396e-7,0.00006610593,0.9917465,0.003211447,0.00005204366,0.0006486975,0.004062836],"study_design_scores_gemma":[0.001149013,0.0002465542,0.00000816854,0.000006575294,0.00004606598,0.000002330627,0.000008676134,0.9417066,0.050771,0.00004688594,0.005788756,0.0002193597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007432053,0.000330653,0.9904014,0.00008378526,0.0006858641,0.0004789215,0.000124877,0.0004176248,0.00004475248],"genre_scores_gemma":[0.9819275,0.0003802652,0.01716639,0.00008631776,0.00006988636,0.0001340739,0.0001486603,0.00005762516,0.0000293425],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9744954,"threshold_uncertainty_score":0.8569404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007581228227327198,"score_gpt":0.203131640112971,"score_spread":0.1955504118856438,"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."}}