{"id":"W2088004202","doi":"10.1109/naps.2007.4402283","title":"Stationary Wavelet Transform Based HVDC Line Protection","year":2007,"lang":"en","type":"article","venue":"","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Wavelet transform; Rectifier (neural networks); Wavelet; Line (geometry); Relay; Distortion (music); Computer science; Electronic engineering; Stationary wavelet transform; Algorithm; Control theory (sociology); Discrete wavelet transform; Engineering; Mathematics; Artificial intelligence; Physics; Artificial neural network; Power (physics)","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":[0.0001520675,0.0003764832,0.0003428735,0.0003434113,0.0001593536,0.0004522529,0.0003473986,0.0003766519,0.001351682],"category_scores_gemma":[0.0004173349,0.0001240508,0.0002552141,0.0003714945,0.000209355,0.0005377021,0.0001735837,0.0003913999,0.0007892302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000204782,"about_ca_system_score_gemma":0.0002739496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005577354,"about_ca_topic_score_gemma":0.0004911824,"domain_scores_codex":[0.9998708,0.00001698547,0.000006819575,0.00002789923,0.00006727393,0.00001028458],"domain_scores_gemma":[0.9998832,0.00002220275,0.00001793085,0.00001442216,0.00005529414,0.00000700842],"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":[0.0003071038,0.00007384909,0.0006249116,0.0001634563,0.00003652662,0.0002334238,0.00006844895,0.08139704,0.1777834,0.01388321,0.003552748,0.7218759],"study_design_scores_gemma":[0.00003430001,0.0002053231,0.001008324,0.00001149823,0.00003105659,0.000464481,0.00002023556,0.9308609,0.05686529,0.002905085,0.007578562,0.00001499864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02324135,0.0002741877,0.9734088,0.00006655654,0.00006552799,0.00002087543,0.00003898533,0.0004208898,0.002462933],"genre_scores_gemma":[0.5176799,0.0008474711,0.4719322,0.00008196646,0.0001071558,0.00003694684,0.0003321046,0.0001092637,0.00887309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001351682,"threshold_uncertainty_score":0.004521847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01086064324296851,"score_gpt":0.2198208658979214,"score_spread":0.2089602226549528,"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."}}