{"id":"W2906428308","doi":"10.1109/pesgm.2018.8586305","title":"A Fast Self-synchronizing Synchronverter Design with Easily Tuneable Parameters","year":2018,"lang":"en","type":"article","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Synchronizing; Computer science; Control theory (sociology); Controller (irrigation); Synchronization (alternating current); Inductance; Grid; Process (computing); Voltage; Engineering; Channel (broadcasting); Electrical engineering","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":[0.00007398323,0.0001589454,0.0001365923,0.00005907578,0.00007013373,0.00007243206,0.0001012199,0.00005579623,0.0002844372],"category_scores_gemma":[0.000003133156,0.0001248605,0.00002706995,0.000157825,0.00003473617,0.0002087059,0.00001178355,0.00006901357,0.000255697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007262622,"about_ca_system_score_gemma":0.0000224768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002123831,"about_ca_topic_score_gemma":0.00002038424,"domain_scores_codex":[0.9992854,0.00001725713,0.0001273947,0.0001696842,0.00009964743,0.0003006453],"domain_scores_gemma":[0.9996454,0.00002426237,0.00001669113,0.0001889757,0.00005284072,0.00007185653],"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":[0.0001514196,0.0001088619,0.001140226,0.0001644006,0.0006873688,0.00003257465,0.002085848,0.8813579,0.01055668,0.0002072208,0.01909916,0.08440833],"study_design_scores_gemma":[0.0005865375,0.0001609189,0.0001123573,0.00002426326,0.00003448231,0.00001669986,0.00003750026,0.9893824,0.007899583,0.00001366591,0.001505022,0.0002264953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01115909,0.0002488462,0.979961,0.00003366444,0.0001512579,0.000236922,0.000001014665,0.0008700418,0.007338156],"genre_scores_gemma":[0.7931002,0.00004694267,0.2063538,0.0001474893,0.0001089299,0.00002713006,0.000002987459,0.00004302413,0.00016948],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7819412,"threshold_uncertainty_score":0.5091663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006935626898328641,"score_gpt":0.1608915221446829,"score_spread":0.1539558952463542,"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."}}