{"id":"W4396213980","doi":"10.2316/j.2023.203-0455","title":"A NEW ADAPTIVE UNDER-FREQUENCY LOAD SHEDDING SCHEME FOR MULTI-AREA POWER SYSTEM, 1-10.","year":2023,"lang":"en","type":"article","venue":"International Journal of Power and Energy Systems","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Load Shedding; Scheme (mathematics); Power (physics); Computer science; Electric power system; Control theory (sociology); Electronic engineering; Engineering; Mathematics; Physics; Control (management); Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004333735,0.0001817617,0.0002983139,0.0003042289,0.00005697778,0.0001419327,0.0002224494,0.0001267756,0.00002020129],"category_scores_gemma":[0.00003680854,0.0001582127,0.0001480905,0.0001500302,0.00001304135,0.0003050589,0.00002588181,0.0001152939,0.0000150751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003860769,"about_ca_system_score_gemma":0.00008077529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003842023,"about_ca_topic_score_gemma":0.00002241534,"domain_scores_codex":[0.9985279,0.0000305765,0.0006206207,0.0001472278,0.0004584489,0.0002151531],"domain_scores_gemma":[0.9989506,0.00006227382,0.0002052676,0.00009620198,0.0005349979,0.0001506626],"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":[0.001290362,0.0002463883,0.001608448,0.001097923,0.01168325,0.001116869,0.01020676,0.4978822,0.1220817,0.1641287,0.1695733,0.01908407],"study_design_scores_gemma":[0.00672736,0.0008007794,0.001058738,0.003839026,0.00009274091,0.002747471,0.01019025,0.7925774,0.001150175,0.0003712006,0.1793598,0.001085024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01673193,0.00305096,0.9624256,0.00008151045,0.01314854,0.0001613879,0.00004852387,0.0002517837,0.004099738],"genre_scores_gemma":[0.9954072,0.00005092416,0.001518263,0.00001017948,0.0008141839,0.0000235339,0.000005159635,0.0000401341,0.002130418],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9786752,"threshold_uncertainty_score":0.6451729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02479132228772597,"score_gpt":0.2606107648804277,"score_spread":0.2358194425927017,"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."}}