{"id":"W2056204895","doi":"10.1016/s0378-7796(02)00173-6","title":"Power quality event detection using Adaline","year":2002,"lang":"en","type":"article","venue":"Electric Power Systems Research","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Power quality; Event (particle physics); Quality (philosophy); Power (physics); Electric power system; Simple (philosophy); Line (geometry); Wavelet; Artificial intelligence; Machine learning; Engineering; Voltage; Electrical engineering; Mathematics","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":[0.0003083998,0.0004972094,0.0004020191,0.001114104,0.000349726,0.0005488477,0.0004718621,0.000426856,0.006280226],"category_scores_gemma":[0.0009632261,0.0002002913,0.0001459036,0.0005015817,0.0001338599,0.0005161306,0.0002616267,0.0003337879,0.001798128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000255154,"about_ca_system_score_gemma":0.0001953155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000659433,"about_ca_topic_score_gemma":0.001519614,"domain_scores_codex":[0.9996511,0.0000727521,0.00001764038,0.00008652164,0.0001346556,0.00003740549],"domain_scores_gemma":[0.9988415,0.0002895631,0.0002597521,0.0001644171,0.0003787946,0.00006609926],"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":[0.004714943,0.0004592907,0.03374152,0.000409985,0.0001186026,0.0005975502,0.0003137672,0.008964608,0.221245,0.003194763,0.02551342,0.7007266],"study_design_scores_gemma":[0.0004686324,0.001856961,0.02704619,0.00005632002,0.0001909449,0.001597761,0.0001502541,0.4901291,0.4069221,0.002128979,0.06935015,0.0001025583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2032942,0.0005880326,0.7234078,0.0002881763,0.0002912603,0.0001571066,0.001345664,0.05047786,0.02014992],"genre_scores_gemma":[0.812663,0.0001061819,0.1784277,0.0002007512,0.0001099864,0.00008737544,0.0009666956,0.0004250609,0.007013266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006280226,"threshold_uncertainty_score":0.02100939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1500631846505895,"score_gpt":0.374102493973354,"score_spread":0.2240393093227645,"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."}}