{"id":"W4309227274","doi":"10.1109/globconpt57482.2022.9938168","title":"A High Speed Method for Loss of Excitation Detection","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Generator (circuit theory); Robustness (evolution); Control theory (sociology); Excitation; Shunt generator; Armature (electrical engineering); Computer science; Electric power system; Permanent magnet synchronous generator; Swing; AC power; Electric generator; Electrical impedance; Power (physics); Engineering; Electrical engineering; Voltage; Electromagnetic coil; Physics; Control (management)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006252723,0.0002541335,0.0003711178,0.0002098675,0.0003868266,0.00005720326,0.0007427536,0.0001680152,0.00002577841],"category_scores_gemma":[0.0001107702,0.0002932357,0.00008285967,0.0006295851,0.0001263743,0.000113722,0.0003033833,0.0004133836,0.000004036085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003647832,"about_ca_system_score_gemma":0.00003231551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001503759,"about_ca_topic_score_gemma":0.00005579131,"domain_scores_codex":[0.9983574,0.0002001599,0.0005240465,0.0003409397,0.0002909408,0.0002865766],"domain_scores_gemma":[0.9984716,0.0001810421,0.0002860782,0.0008568771,0.0001689593,0.00003541595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005264886,0.0003551912,0.0007001999,0.0004282275,0.0005174332,0.000006295016,0.001712098,0.02447504,0.05364828,0.164753,0.004460156,0.7484176],"study_design_scores_gemma":[0.004224472,0.00329322,0.003237368,0.0002497794,0.0001534107,0.0002561393,0.01604386,0.7723547,0.07634728,0.08933651,0.03271235,0.001790877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3931926,0.001011891,0.5971711,0.0004169677,0.001555069,0.001121121,0.0002168872,0.002451362,0.002863006],"genre_scores_gemma":[0.9937879,0.0001231472,0.005859833,0.00003300277,0.00001125054,0.0001104209,0.00002956368,0.00002229554,0.00002255312],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7478797,"threshold_uncertainty_score":0.999952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01617700909257096,"score_gpt":0.2776544461184908,"score_spread":0.2614774370259199,"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."}}