{"id":"W2059615198","doi":"10.1016/j.epsr.2011.02.002","title":"Selection of suitable fuzzy operators for representative power factor evaluation in non-sinusoidal situations","year":2011,"lang":"en","type":"article","venue":"Electric Power Systems Research","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; University of Ontario Institute of Technology","funders":"","keywords":"Fuzzy logic; Harmonics; Power factor; Power (physics); Control theory (sociology); Electric power system; Non-sinusoidal waveform; Selection (genetic algorithm); Computer science; Mathematics; Fuzzy number; Factor (programming language); Mathematical optimization; Fuzzy set; Engineering; Artificial intelligence; Electrical engineering; Voltage","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":[0.003830929,0.00016555,0.0003126541,0.0009118519,0.0001325054,0.00005694181,0.0002606697,0.0002013403,0.0001497984],"category_scores_gemma":[0.000555089,0.0001720428,0.0000723819,0.001905438,0.00003675428,0.0003722257,0.00003141676,0.0004899638,0.00003982246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000621144,"about_ca_system_score_gemma":0.0003102374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007083294,"about_ca_topic_score_gemma":0.000158724,"domain_scores_codex":[0.9970177,0.0005110774,0.0005695486,0.0003256002,0.0008804615,0.0006955775],"domain_scores_gemma":[0.9981912,0.0003849514,0.00006484264,0.0002949882,0.0009580498,0.0001059322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001223151,0.002292626,0.02380589,0.0019522,0.001461067,0.00002533809,0.1553725,0.01909315,0.7079098,0.01864849,0.0637515,0.004464306],"study_design_scores_gemma":[0.005590521,0.002598266,0.08858802,0.0004737699,0.00006881541,0.00003004453,0.008934248,0.5209804,0.3653292,0.002660661,0.003310877,0.001435167],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9646968,0.0009963495,0.01199021,0.00001926989,0.0005724211,0.00301705,0.00005201756,0.0001011048,0.01855481],"genre_scores_gemma":[0.99875,0.00003809114,0.0001441253,0.000002601102,0.00003126369,0.0005612344,0.00001486469,0.00004112317,0.0004166759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5018873,"threshold_uncertainty_score":0.7015702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1361607890742031,"score_gpt":0.3768935160982123,"score_spread":0.2407327270240091,"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."}}