{"id":"W36287277","doi":"","title":"Performance enhancement of digital relays for transmission line distance protection","year":2003,"lang":"en","type":"dissertation","venue":"Memorial University Research Repository (Memorial University)","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland","keywords":"Relay; Digital protective relay; Transmission line; Transmission (telecommunications); Algorithm; Protective relay; Line (geometry); Computer science; Fault (geology); Point (geometry); Electronic engineering; Filter (signal processing); Discrete Fourier transform (general); Fast Fourier transform; SIGNAL (programming language); Electric power transmission; Fourier transform; Engineering; Electrical engineering; Mathematics; Telecommunications; Short-time Fourier transform; Fourier analysis; Computer vision","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004504055,0.0003658443,0.0002386946,0.0003092478,0.000128383,0.0005956483,0.0003000503,0.0003238416,0.001647711],"category_scores_gemma":[0.001996674,0.00008675855,0.0001416055,0.0002049408,0.0001737516,0.0005751177,0.0001866567,0.0001901044,0.000403575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003613747,"about_ca_system_score_gemma":0.0001559711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002794951,"about_ca_topic_score_gemma":0.0002925299,"domain_scores_codex":[0.9997008,0.00008973761,0.0000172416,0.0000420938,0.0001319456,0.00001819732],"domain_scores_gemma":[0.9993492,0.0003638317,0.00006860582,0.00007048889,0.0001342463,0.00001358094],"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":[0.001393367,0.0001645574,0.002323119,0.0003871621,0.0000692869,0.0001867279,0.0002582497,0.2130146,0.2149954,0.01576356,0.001470092,0.5499738],"study_design_scores_gemma":[0.0001011692,0.001052337,0.001873209,0.00003252999,0.00008765501,0.0004264135,0.00004307819,0.8405699,0.1458708,0.002776496,0.007146671,0.00001978204],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3543795,0.001385281,0.6308196,0.0002134143,0.00008630999,0.00005009881,0.00004778092,0.001022569,0.0119955],"genre_scores_gemma":[0.9436263,0.0004841155,0.0533463,0.00001970342,0.00002562815,0.00001391095,0.00003360905,0.00002308119,0.002427288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001647711,"threshold_uncertainty_score":0.005512118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01902648597094412,"score_gpt":0.2400038909182917,"score_spread":0.2209774049473476,"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."}}