{"id":"W1598130868","doi":"10.1109/pes.2003.1267428","title":"Adaptive and artificial intelligence based PSS","year":2004,"lang":"en","type":"article","venue":"2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491)","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Control theory (sociology); Operating point; Transfer function; Linear system; Electric power system; Controller (irrigation); Computer science; Control engineering; Permanent magnet synchronous generator; Adaptive control; Generator (circuit theory); Power (physics); Engineering; Mathematics; Artificial intelligence; Voltage; Control (management); Electronic 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000701689,0.0006232209,0.0005357785,0.000107188,0.0002005116,0.0001513008,0.0003119089,0.0003439976,0.00004567385],"category_scores_gemma":[0.0001927485,0.000691979,0.0002529998,0.0007682841,0.0001076806,0.0002451988,0.0000335481,0.0004476775,0.00008444346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005069175,"about_ca_system_score_gemma":0.0001344025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005798918,"about_ca_topic_score_gemma":0.00001175395,"domain_scores_codex":[0.9972296,0.00005592591,0.0007591657,0.0006518786,0.0004310946,0.0008722915],"domain_scores_gemma":[0.9985681,0.0001082673,0.00009624812,0.0005142047,0.0003522692,0.0003608667],"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":[0.000009446473,0.00004903932,0.00005986927,0.0001446556,0.00008965883,0.000006800934,0.001081332,0.9619741,0.03488541,0.0003684781,0.001141592,0.0001895872],"study_design_scores_gemma":[0.000313969,0.00007286041,0.00009877633,0.0001672626,0.00003508162,0.00001225081,0.0001787238,0.9605563,0.03673473,0.00005245169,0.0009494019,0.00082824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2307638,0.0003276091,0.7611153,0.00009913742,0.005134746,0.0005052142,0.00005725748,0.001188988,0.0008080523],"genre_scores_gemma":[0.8269453,0.00008604924,0.172077,0.0001980832,0.0003327606,0.00007943894,0.00001787167,0.0001568202,0.0001067087],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5961816,"threshold_uncertainty_score":0.9995531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01326021557409329,"score_gpt":0.2111969838254201,"score_spread":0.1979367682513268,"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."}}