{"id":"W2980140799","doi":"10.1109/ccece.2019.8861772","title":"Is It Enough to just Rely on Near-End, Middle, and Far-End Points to get Feasible Relay Coordination?","year":2019,"lang":"en","type":"article","venue":"","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Relay; Backup; Margin (machine learning); Computer science; Integer (computer science); Mathematical optimization; Fault (geology); Power (physics); Optimization problem; Nonlinear system; Protective relay; Electric power system; Cutting-plane method; Integer programming; Mathematics; Algorithm","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":[0.002522025,0.001179011,0.001991129,0.0004634714,0.0005938666,0.002075203,0.001426659,0.002023446,0.004770527],"category_scores_gemma":[0.008686376,0.0005790181,0.0006293986,0.0004267026,0.00162027,0.006983479,0.001239276,0.001447805,0.002550256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004520497,"about_ca_system_score_gemma":0.0007627027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004289706,"about_ca_topic_score_gemma":0.0004418893,"domain_scores_codex":[0.9984872,0.0005709811,0.00008927951,0.0004403738,0.0002677181,0.0001443845],"domain_scores_gemma":[0.9948857,0.003012139,0.000547145,0.0007356753,0.0006418304,0.0001774611],"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":[0.001097552,0.0002402609,0.002357304,0.001360844,0.0001415128,0.0002954226,0.0003757569,0.257137,0.03735515,0.2139269,0.006652719,0.4790596],"study_design_scores_gemma":[0.000315711,0.002486419,0.001902041,0.0007184476,0.0002092821,0.00153621,0.0008413328,0.5693922,0.0353002,0.3489885,0.0381151,0.0001944977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01190124,0.001145707,0.9811452,0.0009879636,0.0001142964,0.00003285681,0.00002837412,0.0001215354,0.004522725],"genre_scores_gemma":[0.5436126,0.002909154,0.4474205,0.0006206648,0.0004966194,0.000144488,0.0001166723,0.0002763388,0.004403106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004770527,"threshold_uncertainty_score":0.01595896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02457684006347728,"score_gpt":0.2583072783163392,"score_spread":0.2337304382528619,"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."}}