{"id":"W4391150536","doi":"10.1049/icp.2023.3226","title":"New indices for voltage sags in distribution systems","year":2023,"lang":"en","type":"article","venue":"IET conference proceedings.","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Smart grid; Power quality; Computer science; Voltage; Grid; Distribution grid; Reliability engineering; Set (abstract data type); Voltage sag; Power (physics); Quality (philosophy); Electric power system; Distribution (mathematics); Electronic engineering; Engineering; 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":[0.001988055,0.001384747,0.0009954524,0.006819239,0.0004494386,0.002555786,0.0009894543,0.0007691383,0.003389967],"category_scores_gemma":[0.006740673,0.0002446689,0.0006931676,0.004018755,0.0006960498,0.003725023,0.001206058,0.001258699,0.001871231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007995574,"about_ca_system_score_gemma":0.0005243291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001107549,"about_ca_topic_score_gemma":0.001326077,"domain_scores_codex":[0.9974597,0.0004388282,0.0003156634,0.0002571453,0.001412507,0.0001161846],"domain_scores_gemma":[0.9962187,0.001014506,0.0007334501,0.0003970675,0.001485908,0.0001503526],"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":[0.0006282328,0.0003435388,0.03177024,0.001256794,0.0003679466,0.0003191655,0.0007059883,0.05538142,0.04153393,0.05966218,0.02946066,0.7785699],"study_design_scores_gemma":[0.0001687049,0.001421226,0.07894359,0.0009126478,0.0004686837,0.002762773,0.001042407,0.4819544,0.04852382,0.07007645,0.3131549,0.0005703954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04645266,0.00859502,0.8963245,0.0005223217,0.00145241,0.0004773215,0.003769816,0.003382085,0.0390239],"genre_scores_gemma":[0.4155793,0.005487347,0.5571482,0.0003059187,0.001197596,0.0006511754,0.007188915,0.0005636056,0.01187797],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006819239,"threshold_uncertainty_score":0.0113405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04348165175307881,"score_gpt":0.2634586258139641,"score_spread":0.2199769740608853,"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."}}