{"id":"W2136072287","doi":"10.1109/tpwrd.2003.823188","title":"Transmission Line Distance Protection Using Wavelet Transform Algorithm","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Transmission line; Electric power transmission; Protective relay; Line (geometry); Transmission (telecommunications); Electronic engineering; Computer science; Wavelet transform; Algorithm; Wavelet; Microprocessor; Digital protective relay; Power-system protection; Engineering; Electrical engineering; Relay; Telecommunications; Electric power system; Computer hardware; Mathematics; Artificial intelligence","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":[0.0003385906,0.000465954,0.0004732003,0.0005165191,0.0002173672,0.0007642388,0.0004437676,0.000620472,0.00186089],"category_scores_gemma":[0.001079053,0.0001717713,0.000335275,0.0006909829,0.0002826971,0.0009949935,0.0004590219,0.0006759785,0.0008749423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002435733,"about_ca_system_score_gemma":0.0004391427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006114341,"about_ca_topic_score_gemma":0.0003548436,"domain_scores_codex":[0.9997606,0.00004052643,0.00001701622,0.00004751487,0.0001160406,0.00001823036],"domain_scores_gemma":[0.9998073,0.0000667687,0.00002688333,0.00002912231,0.00006123501,0.00000862221],"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":[0.0001902154,0.00007392735,0.0003672299,0.0001380992,0.00005308471,0.0001386569,0.00009602377,0.1763457,0.05396824,0.04170102,0.002824947,0.7241029],"study_design_scores_gemma":[0.00003701135,0.00009519394,0.0002168271,0.00001383616,0.00001477304,0.0001629163,0.00001246826,0.975005,0.01154094,0.007928888,0.004960913,0.00001114678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003756081,0.0001123631,0.9950323,0.00004210287,0.00002391033,0.00001426262,0.000008629515,0.0001630612,0.0008472526],"genre_scores_gemma":[0.1858754,0.0006938049,0.8085171,0.00004782672,0.00007977268,0.0001098473,0.000140848,0.00008405498,0.004451413],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00186089,"threshold_uncertainty_score":0.006225288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01317562100044199,"score_gpt":0.2176447098727664,"score_spread":0.2044690888723243,"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."}}