{"id":"W4387788296","doi":"10.23977/jeeem.2023.060505","title":"Research on Fault Diagnosis and Transient Stability Evaluation of Power System Based on Machine Learning","year":2023,"lang":"en","type":"article","venue":"Journal of Electrotechnology Electrical Engineering and Management","topic":"Smart Grid and Power Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fault (geology); Transient (computer programming); Electric power system; Stability (learning theory); Reliability engineering; Computer science; Power (physics); Fault indicator; Machine learning; Artificial intelligence; Engineering; Control engineering; Fault detection and isolation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008281466,0.0006581283,0.0008717622,0.00150462,0.0003945158,0.001206486,0.000738633,0.0007539454,0.001011115],"category_scores_gemma":[0.00237367,0.0002233039,0.0007427927,0.00197621,0.0007118816,0.002478176,0.0003866319,0.0007952376,0.0002552577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008840208,"about_ca_system_score_gemma":0.0006694666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00308825,"about_ca_topic_score_gemma":0.001045821,"domain_scores_codex":[0.998758,0.0001985767,0.0001007309,0.0003353817,0.000524878,0.00008258038],"domain_scores_gemma":[0.9988438,0.0005144998,0.0001152152,0.00007630958,0.0004172817,0.00003287434],"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":[0.0001323814,0.0001375339,0.007910826,0.001054281,0.0001710424,0.0002091239,0.0002521489,0.2494411,0.01006514,0.03299036,0.00293906,0.6946971],"study_design_scores_gemma":[0.00001239463,0.0001135281,0.004193381,0.0000885034,0.00006308607,0.0001680477,0.0000852775,0.9629282,0.00672622,0.02051445,0.00505855,0.00004830869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04517802,0.02475931,0.9177677,0.001046142,0.0003378497,0.00007040922,0.0001008389,0.0006327501,0.01010692],"genre_scores_gemma":[0.883954,0.021814,0.08890877,0.0002378108,0.0007386482,0.00008417815,0.0002783906,0.00006974116,0.00391436],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00308825,"threshold_uncertainty_score":0.006414115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02587697358108266,"score_gpt":0.2716957578249239,"score_spread":0.2458187842438412,"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."}}