{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005440983,0.0004514615,0.0006437681,0.001254985,0.0007905828,0.00009305766,0.0007256843,0.0007871193,0.00002063573],"category_scores_gemma":[0.00007659256,0.0005812863,0.0003500531,0.00138976,0.0001438236,0.0009524177,0.00004943467,0.0009584003,0.00001477355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002002724,"about_ca_system_score_gemma":0.0005030176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001253008,"about_ca_topic_score_gemma":0.00005932606,"domain_scores_codex":[0.9968576,0.0002764646,0.0004640806,0.0007212519,0.001019552,0.0006610471],"domain_scores_gemma":[0.9978613,0.000135763,0.0002635623,0.0005369196,0.0009433188,0.0002591914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0595113,0.00136242,0.0001430013,0.01915597,0.002373093,0.0008074225,0.005371908,0.004358585,0.7878066,0.001941188,0.01280805,0.1043605],"study_design_scores_gemma":[0.003233865,0.001240881,0.00001461499,0.000691353,0.0001932389,0.00001031792,0.001663756,0.00574586,0.2944632,0.00002450242,0.6920287,0.0006897052],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6895242,0.000260934,0.08880299,0.00001909793,0.04318109,0.007996364,0.0002370486,0.0006798509,0.1692984],"genre_scores_gemma":[0.826544,0.0003582986,0.0002682637,3.372171e-7,0.002059289,0.00001087299,0.0004007593,0.0001197782,0.1702384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6792206,"threshold_uncertainty_score":0.9996638,"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."}}