{"id":"W2898635019","doi":"10.1109/cpem.2018.8500803","title":"Calibration of Electricity Meters with Digital Input","year":2018,"lang":"en","type":"article","venue":"","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Metering mode; Smart grid; Electrical engineering; Electricity; Power electronics; Electronics; Waveform; IEC 61850; Engineering; Computer science; Electronic engineering; Voltage; Automation","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":[0.00002641441,0.00003653716,0.00005108992,0.00002294511,0.000009073235,0.00001377619,0.00003519714,0.00001939087,0.00003450102],"category_scores_gemma":[0.000004950057,0.00002888058,0.00001052356,0.00009437604,0.00002342489,0.0001724083,0.00000431994,0.00002755615,0.000006968651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009149431,"about_ca_system_score_gemma":0.000006905407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007146213,"about_ca_topic_score_gemma":0.00001415563,"domain_scores_codex":[0.9997674,0.000002687145,0.00006735785,0.00003790589,0.00005681629,0.00006781166],"domain_scores_gemma":[0.9998831,0.0000110838,0.000008054268,0.00006279337,0.00001587367,0.00001905096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001041282,0.001085196,0.05973887,0.001485843,0.00275436,0.00003304067,0.02444673,0.02303248,0.4212308,0.1978711,0.09633625,0.170944],"study_design_scores_gemma":[0.0004124054,0.0004276065,0.002300245,0.0000150621,0.00001790456,0.000004909098,0.00006757179,0.174551,0.8150022,0.0006468635,0.0062912,0.0002630059],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6904737,0.00001090228,0.2822545,0.0000259831,0.00003850665,0.00003515947,0.000004622194,0.0001302601,0.02702634],"genre_scores_gemma":[0.999161,0.000002285507,0.0006879474,0.00002910235,0.00001869258,6.542225e-7,0.000002940489,0.000005317881,0.00009202852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3937714,"threshold_uncertainty_score":0.1177716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01395656503468747,"score_gpt":0.2089264292115828,"score_spread":0.1949698641768954,"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."}}