{"id":"W2161725020","doi":"10.1016/j.ijepes.2006.03.005","title":"Combined detailed and quasi steady-state time simulations for large-disturbance analysis","year":2006,"lang":"en","type":"article","venue":"International Journal of Electrical Power & Energy Systems","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hydro-Québec","funders":"Hydro-Québec","keywords":"Disturbance (geology); Control theory (sociology); Term (time); Steady state (chemistry); Discrete time and continuous time; Electric power system; Interval (graph theory); Computer science; Power (physics); Simple (philosophy); Steady State theory; Mathematics; Control (management); Physics; Statistics; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003224247,0.0001634928,0.0004364553,0.000438976,0.00005209228,0.0001334308,0.0002344795,0.00007662837,0.00003355342],"category_scores_gemma":[0.00008435496,0.0001467261,0.0002150156,0.0004340193,0.00001638722,0.0002001685,0.00001443945,0.0001031953,0.000002204185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002005414,"about_ca_system_score_gemma":0.00003441912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003498527,"about_ca_topic_score_gemma":0.00004238853,"domain_scores_codex":[0.998254,0.00008418046,0.0008659379,0.0001519654,0.0004185783,0.0002253237],"domain_scores_gemma":[0.9985119,0.0002888977,0.0002712116,0.0001222516,0.000704826,0.0001009003],"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":[0.0001814563,0.0002762295,0.01044237,0.00001526893,0.001886368,0.00001845612,0.00009311028,0.9688898,0.0009222155,0.01382823,0.003340664,0.0001058219],"study_design_scores_gemma":[0.001238907,0.0001244282,0.003223433,0.00002053642,0.0001272135,0.00002117188,0.000009625392,0.9780079,0.0001262249,0.0003605731,0.01655159,0.0001883588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0490416,0.001564254,0.9467306,0.0001051744,0.001038238,0.0001383911,0.0001214536,0.00007341124,0.001186947],"genre_scores_gemma":[0.9985901,0.00001670512,0.0002541085,0.00002624196,0.00009709228,0.000008229438,0.00004756488,0.00002149131,0.0009384932],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9495485,"threshold_uncertainty_score":0.5983318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004302585799789305,"score_gpt":0.216934040454451,"score_spread":0.2126314546546617,"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."}}