{"id":"W2127785382","doi":"10.1109/pes.2008.4596920","title":"Model Prediction Adaptive Control for wide-area power system stability enhancement","year":2008,"lang":"en","type":"article","venue":"","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Stability (learning theory); Electric power system; Control theory (sociology); Power (physics); Computer science; Generator (circuit theory); Control engineering; Electricity generation; Power control; Electricity; Control (management); Engineering; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003573033,0.0003089195,0.0002386925,0.0001286436,0.0001642561,0.0003071378,0.0002945075,0.0002154499,0.0009039591],"category_scores_gemma":[0.0006905892,0.0001092843,0.0001517531,0.000166782,0.0002331445,0.0002662039,0.0002703492,0.0004636032,0.0001087979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001973379,"about_ca_system_score_gemma":0.0003031361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002310399,"about_ca_topic_score_gemma":0.002574942,"domain_scores_codex":[0.9998521,0.00004400454,0.000006071986,0.00003279418,0.00005052536,0.00001450808],"domain_scores_gemma":[0.9998125,0.00009520299,0.00003194547,0.00001612515,0.00003759178,0.000006665488],"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":[0.0001204016,0.00008417075,0.0005488052,0.0000541969,0.00003256002,0.00005516547,0.00005976289,0.8388068,0.01675599,0.005941545,0.0009231234,0.1366175],"study_design_scores_gemma":[0.00000772056,0.00004697873,0.0001354813,0.000001663764,0.000003808158,0.000007222838,0.000002447577,0.9977976,0.001002809,0.0006761755,0.0003161383,0.000002058253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07305444,0.000490144,0.920266,0.0002483893,0.00005872264,0.00003275912,0.00001920494,0.0006437612,0.00518663],"genre_scores_gemma":[0.984654,0.0001267988,0.01412999,0.00002793628,0.00002350309,0.00002702332,0.00001190953,0.000009107214,0.0009897845],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002310399,"threshold_uncertainty_score":0.004593909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02840827761722462,"score_gpt":0.1987783850751635,"score_spread":0.1703701074579388,"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."}}