{"id":"W1660591014","doi":"10.1109/pesgm.2015.7285882","title":"An improved harmonic contribution estimation using nonlinear optimization techniques","year":2015,"lang":"en","type":"article","venue":"","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro One (Canada); Kinectrics (Canada)","funders":"","keywords":"Nonlinear system; MATLAB; Harmonic; Computer science; Harmonic analysis; Range (aeronautics); Software; Focus (optics); Voltage; Electronic engineering; Control theory (sociology); Mathematical optimization; Engineering; Mathematics; Electrical engineering; Acoustics; Artificial intelligence; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002882451,0.00009336515,0.00009898429,0.00005721241,0.00003833403,0.00005968115,0.00007012938,0.0000985358,0.00001879232],"category_scores_gemma":[0.00003819812,0.00009732208,0.00002042749,0.0001151194,0.00001353643,0.0005169471,0.000009260299,0.00008340598,0.000008101817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001619871,"about_ca_system_score_gemma":0.00003550619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000333187,"about_ca_topic_score_gemma":0.000005238539,"domain_scores_codex":[0.9994527,0.00002450127,0.0001826551,0.00009854839,0.00009300283,0.0001485538],"domain_scores_gemma":[0.9996003,0.00000818141,0.00002701512,0.0001502081,0.000119436,0.00009485684],"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":[0.0000111923,0.00003481958,0.00001720112,0.00001442391,0.00001187871,6.751198e-7,0.0001443014,0.9717362,0.02291054,0.0003706611,0.0001082035,0.004639925],"study_design_scores_gemma":[0.0001883527,0.00003560478,0.000007448554,0.000007221177,0.00001189942,0.000003072146,0.00002826256,0.90086,0.09822027,0.0001906659,0.0003274992,0.0001196991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04415337,0.00006301036,0.954065,0.00003199456,0.0001324073,0.0001630452,0.000009144213,0.0009772079,0.0004047843],"genre_scores_gemma":[0.6553432,0.00001405481,0.3444004,0.00004168546,0.00005394621,0.000005988984,0.0001156568,0.00001703089,0.000008068786],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6111898,"threshold_uncertainty_score":0.3968679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03791690369833237,"score_gpt":0.2962159430295309,"score_spread":0.2582990393311985,"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."}}