{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004498643,0.0007556407,0.0004491208,0.00169747,0.0003817356,0.0009196063,0.0008913917,0.0007011941,0.01238542],"category_scores_gemma":[0.001402319,0.000281031,0.0002060848,0.0009073513,0.0002511224,0.0009993479,0.0006359002,0.0007073241,0.003884443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003449686,"about_ca_system_score_gemma":0.0003773887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006571002,"about_ca_topic_score_gemma":0.0009284976,"domain_scores_codex":[0.9992798,0.00007404164,0.00003316783,0.0001350234,0.0004372781,0.00004075365],"domain_scores_gemma":[0.9992762,0.000159405,0.00008753509,0.0001431408,0.0003052234,0.00002844188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004224922,0.0001004086,0.001587663,0.000333175,0.00003492058,0.0001876896,0.000199131,0.006384903,0.1161927,0.007036021,0.01213494,0.855386],"study_design_scores_gemma":[0.0002211862,0.0006353977,0.006244658,0.0001414148,0.00007853612,0.002711243,0.0002064363,0.6001027,0.2729485,0.009396934,0.1071403,0.0001725373],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009703885,0.0003899925,0.9751506,0.0001223719,0.0002797301,0.0002120749,0.0002234344,0.007200378,0.006717619],"genre_scores_gemma":[0.3037853,0.000356154,0.6734511,0.000171222,0.000109139,0.0003521239,0.0005301625,0.0004302344,0.02081461],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01238542,"threshold_uncertainty_score":0.04143339,"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."}}