{"id":"W1997709308","doi":"10.1109/tsg.2013.2296598","title":"A New Approach Based on Wavelet Design and Machine Learning for Islanding Detection of Distributed Generation","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Islanding Detection in Power Systems","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Islanding; Wavelet; Process (computing); Computer science; Wavelet transform; Machine learning; Artificial intelligence; Filter bank; Filter (signal processing); Distributed generation; Engineering; Control engineering","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":[0.0003736966,0.000168365,0.0001975555,0.000243999,0.0001935297,0.00003735394,0.00004895385,0.0001106666,0.00001192399],"category_scores_gemma":[0.00001985027,0.0001712822,0.0000725502,0.0002006253,0.00001311579,0.00007308771,3.296962e-7,0.0002097261,0.00000577642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008624565,"about_ca_system_score_gemma":0.00001044043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000309034,"about_ca_topic_score_gemma":0.00001789245,"domain_scores_codex":[0.9991218,0.00009301359,0.0002571407,0.0002142475,0.0001458077,0.0001679988],"domain_scores_gemma":[0.9994925,0.000192739,0.00005478197,0.0001571356,0.0000424674,0.00006040787],"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":[0.00009065014,0.0000214787,0.000007770474,0.0000778196,0.00003388232,9.834207e-8,0.00008988026,0.9537043,0.03532297,0.000005372583,0.0003083967,0.01033739],"study_design_scores_gemma":[0.0007458836,0.0002627998,0.00001721621,0.0000259484,0.0000320416,0.000005913625,0.000007625318,0.7907186,0.2061205,0.000004911129,0.001928539,0.0001300103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003200048,0.000009969547,0.9941219,0.00001345973,0.001867962,0.0003983389,0.00003584664,0.0002433245,0.0001091215],"genre_scores_gemma":[0.9900653,0.000005470661,0.009414701,0.00001040456,0.0002309045,0.0001052266,0.00003005087,0.00004265899,0.00009525137],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9868653,"threshold_uncertainty_score":0.6984687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02360540020301082,"score_gpt":0.2076891709990345,"score_spread":0.1840837707960237,"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."}}