{"id":"W3004883211","doi":"10.1109/tpwrd.2020.2971151","title":"Open Phase Detection in DER Operation by Using Power Quality Data Analytics","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro One (Canada)","funders":"","keywords":"Benchmarking; Anomaly detection; Analytics; Computer science; Transformer; Reliability engineering; Data mining; Real-time computing; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002063565,0.000822214,0.000491039,0.002567953,0.000308656,0.001931143,0.0007513916,0.0005112019,0.0008101418],"category_scores_gemma":[0.006658979,0.0001894154,0.0002947603,0.001757099,0.0003951032,0.002792509,0.001201969,0.000909392,0.0007174863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004591325,"about_ca_system_score_gemma":0.0004738997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001152882,"about_ca_topic_score_gemma":0.001679964,"domain_scores_codex":[0.9986736,0.0003382845,0.0001267994,0.0002393946,0.000541752,0.00008020709],"domain_scores_gemma":[0.9960751,0.001451324,0.000595602,0.0005383888,0.001241097,0.00009841774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003342624,0.0003378866,0.07065465,0.0003518256,0.0001034129,0.0003682203,0.0006856428,0.09154516,0.02387914,0.01277937,0.007069769,0.7918906],"study_design_scores_gemma":[0.00003671535,0.0002788091,0.01824008,0.0001802551,0.00004877744,0.0004637196,0.0007897695,0.8904971,0.04563042,0.02542742,0.01833549,0.00007129909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1347796,0.0007786385,0.8492858,0.001320051,0.0001465455,0.0002501558,0.0009444241,0.003676837,0.008817911],"genre_scores_gemma":[0.8023051,0.0005027272,0.1944371,0.0001814884,0.0001070624,0.00006378015,0.001271501,0.0001632737,0.0009680419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002567953,"threshold_uncertainty_score":0.01091337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1649539311792147,"score_gpt":0.3499929023001594,"score_spread":0.1850389711209447,"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."}}