{"id":"W1821265355","doi":"10.1109/pesw.2002.985254","title":"Calibration system for power quality instrumentation","year":2003,"lang":"en","type":"article","venue":"2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Harmonics; Revenue; Calibration; Reliability engineering; Computer science; Electric power system; Field (mathematics); Quality (philosophy); Deregulation; Power (physics); Waveform; Instrumentation (computer programming); Electrical engineering; Systems engineering; Voltage; Engineering; Finance; Business","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":[0.007321344,0.001181343,0.001131983,0.003292008,0.001383457,0.002299346,0.002108179,0.002414196,0.02475405],"category_scores_gemma":[0.0176801,0.0005192739,0.0005259158,0.002500975,0.001217464,0.002711034,0.002193297,0.002430789,0.01778417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001422986,"about_ca_system_score_gemma":0.001734498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004927259,"about_ca_topic_score_gemma":0.0003594788,"domain_scores_codex":[0.98715,0.003278048,0.0008581759,0.002100314,0.00619828,0.000415147],"domain_scores_gemma":[0.9876528,0.002784809,0.0008831327,0.003184318,0.005264884,0.0002300618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001573285,0.0005274191,0.01009427,0.001484257,0.0001093805,0.0006724161,0.001377353,0.005239695,0.2415841,0.07620282,0.0626919,0.5984431],"study_design_scores_gemma":[0.0005465705,0.001938383,0.01064782,0.0006255727,0.0002034255,0.00357905,0.0002589776,0.05684309,0.2866693,0.01167304,0.6267164,0.0002984018],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01344248,0.001227149,0.9255486,0.0005073389,0.001125708,0.001651771,0.0009988471,0.02322309,0.03227503],"genre_scores_gemma":[0.3317824,0.001717095,0.5968224,0.003006855,0.001345346,0.005067712,0.004430168,0.003418857,0.05240911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02475405,"threshold_uncertainty_score":0.08281052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02229549044219105,"score_gpt":0.2408828920918285,"score_spread":0.2185874016496375,"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."}}