{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003673777,0.0002142774,0.0002687403,0.0001083936,0.0001329948,0.0001779762,0.0005714187,0.0001532179,0.0003473415],"category_scores_gemma":[0.00001041712,0.0002519318,0.00006020235,0.0003896672,0.00003192417,0.001213474,0.00001153951,0.0004504742,0.00007487401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001804959,"about_ca_system_score_gemma":0.0000564683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002554862,"about_ca_topic_score_gemma":0.0003054957,"domain_scores_codex":[0.9984882,0.0001158325,0.0004861743,0.0004168076,0.0002301888,0.0002627922],"domain_scores_gemma":[0.9991629,0.00006398053,0.00004424128,0.0005358808,0.00004265615,0.0001503252],"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":[0.0008320024,0.001432947,0.00001905608,0.000138912,0.0005287437,0.00004180029,0.004709727,0.5683845,0.3911383,0.00003263833,0.004633637,0.02810769],"study_design_scores_gemma":[0.002523679,0.000192831,0.00003671924,0.00003657849,0.00009666004,0.000006034356,0.0004350574,0.8796952,0.1084852,0.00001449782,0.007892231,0.000585308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2505493,0.0001269781,0.7473589,0.0002190681,0.0004789127,0.0002735526,0.000559324,0.0001450116,0.000288958],"genre_scores_gemma":[0.9985144,0.0001026021,0.0005470417,0.0006990767,0.00001564588,0.000008878707,0.00004844868,0.00004110184,0.00002279119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.747965,"threshold_uncertainty_score":0.9999933,"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."}}