{"id":"W2591489243","doi":"10.1109/tsg.2017.2672881","title":"A New Approach for Fault Classification in Microgrids Using Optimal Wavelet Functions Matching Pursuit","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":135,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wavelet; Particle swarm optimization; Computer science; Wavelet transform; Decision tree; Artificial intelligence; Discrete wavelet transform; Matching pursuit; Machine learning; Fault (geology); Pattern recognition (psychology); Matching (statistics); Support vector machine; Electric power system; Engineering; Power (physics); Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009367053,0.0007720867,0.001008321,0.001362567,0.0003552327,0.0008959404,0.0008602996,0.0007950697,0.0009530054],"category_scores_gemma":[0.001742759,0.0003330621,0.0008050316,0.001262866,0.0005059116,0.001373631,0.001031522,0.0009020396,0.0004720116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004368461,"about_ca_system_score_gemma":0.0006080241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001216932,"about_ca_topic_score_gemma":0.000841238,"domain_scores_codex":[0.999388,0.0001217914,0.000045532,0.0001188795,0.0002790695,0.00004679982],"domain_scores_gemma":[0.9995899,0.00013567,0.00005908393,0.00004640206,0.0001453848,0.0000236502],"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":[0.0001681433,0.0001409853,0.002130497,0.0002039398,0.0001316174,0.0001429723,0.0001249818,0.3202496,0.0237542,0.02815071,0.001935873,0.6228664],"study_design_scores_gemma":[0.000004963421,0.00003329245,0.0001938424,0.000004214145,0.000007412669,0.00002566302,0.00000986745,0.9948908,0.001267446,0.002769834,0.0007876611,0.000005037772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003224662,0.00007890558,0.9961371,0.00004318897,0.00001812321,0.00001412408,0.00001096254,0.00007567448,0.0003972988],"genre_scores_gemma":[0.2080548,0.000355391,0.7888942,0.00007808626,0.000123612,0.0001058243,0.0001526649,0.00007264916,0.002162803],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001362567,"threshold_uncertainty_score":0.004953802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04324336566664713,"score_gpt":0.2772687758960676,"score_spread":0.2340254102294204,"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."}}