{"id":"W3110874572","doi":"10.1109/tpwrs.2020.3041774","title":"Definition and Classification of Power System Stability – Revisited & Extended","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":1077,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; University of Waterloo","funders":"Engineering and Physical Sciences Research Council","keywords":"Electric power system; Stability (learning theory); Computer science; Task (project management); Power transmission; Power (physics); Control engineering; Power electronics; Work (physics); Control theory (sociology); Reliability engineering; Engineering; Electrical engineering; Voltage; Artificial intelligence; Systems engineering; Machine learning; Mechanical engineering; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001421631,0.000152472,0.0002642186,0.00008086915,0.0000564701,0.00003834052,0.00006489081,0.0001098234,0.00004539813],"category_scores_gemma":[0.00000507503,0.000152448,0.00006844894,0.0002396498,0.00002655064,0.0001362669,4.984984e-7,0.0001310142,0.00004162498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007060557,"about_ca_system_score_gemma":0.00001120545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009285577,"about_ca_topic_score_gemma":0.00000377076,"domain_scores_codex":[0.9989843,0.00007893247,0.0004264915,0.0002184834,0.0001599021,0.0001319041],"domain_scores_gemma":[0.9994408,0.00004720842,0.00007567851,0.0002339183,0.0001057869,0.00009656155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001027154,0.0006330261,0.0003365682,0.009607234,0.001096801,0.00001099815,0.01168584,0.3333343,0.6274979,0.007099102,0.002680278,0.004990765],"study_design_scores_gemma":[0.004006451,0.0006656688,0.003836405,0.001090387,0.0004263565,0.00008061093,0.003614168,0.9597285,0.01663517,0.00003174721,0.008482176,0.001402393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02850604,0.0007917465,0.9667614,0.00005684764,0.0005742869,0.0004712644,0.0001428702,0.0003987849,0.002296774],"genre_scores_gemma":[0.9994231,0.00008089613,0.0003778099,0.00001549963,0.000009512552,0.00004570177,0.00001294266,0.0000267259,0.00000782837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.970917,"threshold_uncertainty_score":0.6216648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02660456380169959,"score_gpt":0.2050505261884892,"score_spread":0.1784459623867896,"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."}}