{"id":"W2393566967","doi":"","title":"MONTE CARLO METHOD FOR PROBABILISTIC TRANSIENT STABILITY ASSESSMENT","year":2005,"lang":"en","type":"article","venue":"Proceedings of the Csee","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Monte Carlo method; Probabilistic logic; Transient (computer programming); Computer science; Electric power system; Reliability engineering; Stability (learning theory); Fault (geology); Power (physics); Engineering; Mathematics; Statistics; Artificial intelligence; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002711934,0.000915056,0.001154461,0.002092006,0.0007420244,0.001325207,0.0017842,0.001534534,0.01094744],"category_scores_gemma":[0.008888201,0.0005468177,0.001160164,0.00186361,0.0009688039,0.001420112,0.001238549,0.002690962,0.002609528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009319311,"about_ca_system_score_gemma":0.001609362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003238459,"about_ca_topic_score_gemma":0.00252759,"domain_scores_codex":[0.9974446,0.001484787,0.00008194768,0.0001923971,0.0007144486,0.00008178364],"domain_scores_gemma":[0.9964295,0.002675575,0.0001608839,0.0003015494,0.0003700052,0.00006256749],"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":[0.00006109863,0.0000590212,0.0005259856,0.000200286,0.0001275118,0.0001371602,0.00008883187,0.4821708,0.001562717,0.3858558,0.007164166,0.1220466],"study_design_scores_gemma":[0.00001858817,0.00002190898,0.0001180101,0.00004264631,0.00001898222,0.0001164899,0.000009769805,0.8955508,0.0005830258,0.08530548,0.01818578,0.0000285556],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000277592,0.0002349048,0.9972008,0.00005519073,0.00003939037,0.00004414568,0.00004710577,0.0002281594,0.001872704],"genre_scores_gemma":[0.06679145,0.001115703,0.9236232,0.0001739158,0.000211148,0.0008977979,0.0003821211,0.0004170516,0.006387538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01094744,"threshold_uncertainty_score":0.03662282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01627891780322837,"score_gpt":0.2594198077886533,"score_spread":0.2431408899854249,"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."}}