{"id":"W4383704577","doi":"10.33317/ssurj.548","title":"Time-Frequency Transformation Technique with Various Mother Wavelets for DC Fault Analysis in HVDC Transmission Systems","year":2023,"lang":"en","type":"article","venue":"Sir Syed University Research Journal of Engineering & Technology","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quest University Canada","funders":"","keywords":"Fault (geology); Transmission line; Rectifier (neural networks); Electric power transmission; Wavelet; Electronic engineering; Fault detection and isolation; Transmission system; Engineering; Computer science; Transmission (telecommunications); Electrical engineering; Control theory (sociology); Artificial intelligence; Control (management)","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":[],"consensus_categories":[],"category_scores_codex":[0.001270432,0.0001715768,0.0004256383,0.007077601,0.00007994821,0.00002370456,0.0004230186,0.0003607626,0.000004600872],"category_scores_gemma":[0.00005918381,0.0001696568,0.0001181584,0.005702008,0.00005946661,0.000323696,0.00001766605,0.0007967775,0.000006926284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006741617,"about_ca_system_score_gemma":0.00006739068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004321029,"about_ca_topic_score_gemma":0.00002380271,"domain_scores_codex":[0.9985066,0.00006793765,0.000366373,0.0001667483,0.0003869206,0.0005054352],"domain_scores_gemma":[0.99916,0.0001259242,0.00006900811,0.0002222243,0.0003249877,0.00009783746],"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":[0.0001511481,0.00004086168,0.0001512708,0.0005304083,0.0008119699,0.0003792176,0.0008473645,0.775645,0.2169941,0.0005766599,0.0001579341,0.003714081],"study_design_scores_gemma":[0.002574095,0.001128028,0.000539979,0.0008559984,0.000223765,0.000400957,0.001961645,0.9296803,0.02889116,0.0001743187,0.03300885,0.0005608752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2446947,0.0001982847,0.7531502,0.0001393309,0.0001301791,0.0007714008,0.00001626275,0.0006150272,0.0002845745],"genre_scores_gemma":[0.9980732,0.0001182833,0.001592237,3.756855e-7,0.00002877616,0.00001324674,0.000006070874,0.00003929339,0.0001284804],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7533785,"threshold_uncertainty_score":0.6918402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01056819014354631,"score_gpt":0.2414878324284997,"score_spread":0.2309196422849533,"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."}}