{"id":"W4316660408","doi":"10.1109/naps56150.2022.10012264","title":"Compartive Study of Data-Driven Dynamic Load Model Identification Methods Based on Simulated and Actual PMU Data","year":2022,"lang":"en","type":"article","venue":"2022 North American Power Symposium (NAPS)","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Kalman filter; Control theory (sociology); Computer science; Identification (biology); Electric power system; Nonlinear system; Stability (learning theory); Process (computing); Power (physics); 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":[0.002451701,0.0006140261,0.000498619,0.000817118,0.0003453492,0.0006390598,0.0005799386,0.0005897448,0.0006883896],"category_scores_gemma":[0.01357087,0.0002695886,0.000419933,0.0004654819,0.0003295156,0.001580221,0.0005051604,0.0006459779,0.0001844025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000466494,"about_ca_system_score_gemma":0.0004934215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003628752,"about_ca_topic_score_gemma":0.004010691,"domain_scores_codex":[0.9990086,0.0003916826,0.00007691534,0.0001520177,0.0003253329,0.00004546452],"domain_scores_gemma":[0.9916282,0.005337589,0.0003558669,0.00080471,0.001797606,0.00007608298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001116192,0.0006431956,0.03386841,0.0007883645,0.0003959691,0.0001767333,0.0005258844,0.7063251,0.02226645,0.004200236,0.001287393,0.2284061],"study_design_scores_gemma":[0.00002285173,0.0002089157,0.01081382,0.00002103582,0.0000236229,0.00006329264,0.0001106503,0.9778972,0.009792838,0.0004065771,0.0006089329,0.00003024943],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7662256,0.0003937829,0.2282468,0.0001826349,0.0001154848,0.000110324,0.000324366,0.0008489945,0.003552079],"genre_scores_gemma":[0.9791132,0.0001059995,0.01985085,0.00002298192,0.00001232435,0.00005342753,0.0004462113,0.00004853381,0.000346454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003628752,"threshold_uncertainty_score":0.01296598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03076061958590678,"score_gpt":0.3211066169785707,"score_spread":0.2903459973926639,"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."}}