{"id":"W4405092799","doi":"10.1109/tsg.2024.3512456","title":"Power Distribution Network Topology Detection Using Dual-Graph Structure Graph Neural Network Model","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Concordia University","funders":"","keywords":"Topology (electrical circuits); Computer science; Dual (grammatical number); Network topology; Power graph analysis; Graph; Topological graph theory; Voltage graph; Mathematics; Theoretical computer science; Computer network; Line graph; Combinatorics","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":[0.0003915926,0.0005725684,0.0004971225,0.0007730124,0.0001869534,0.0006204484,0.001242728,0.00070642,0.001289984],"category_scores_gemma":[0.001838951,0.0003001261,0.0005060336,0.0006876332,0.0003594738,0.001021868,0.0005677579,0.0008961465,0.0002745856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008643784,"about_ca_system_score_gemma":0.0005689174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008158899,"about_ca_topic_score_gemma":0.007363097,"domain_scores_codex":[0.9997521,0.0000556459,0.00001025396,0.0000991618,0.00005681375,0.00002597915],"domain_scores_gemma":[0.9995424,0.0002050196,0.00007492574,0.00004314198,0.00010892,0.00002569059],"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":[0.00005259705,0.00003015956,0.0009573429,0.00003027258,0.00002495351,0.00005119976,0.00002135533,0.9273478,0.0009945298,0.004124702,0.0009801522,0.06538504],"study_design_scores_gemma":[0.000001151692,0.000002525685,0.00005807391,7.654002e-7,0.000001061398,0.000003579907,0.000001054473,0.9989113,0.00008195078,0.0008697577,0.00006798949,8.932678e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02751889,0.0001612766,0.9696732,0.000206904,0.00003385019,0.00004680294,0.0001992598,0.0006538558,0.001505975],"genre_scores_gemma":[0.822387,0.0002397187,0.1721904,0.0001178896,0.00005213439,0.0001497627,0.000864046,0.00007400935,0.003925078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008158899,"threshold_uncertainty_score":0.01622277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008895301259256345,"score_gpt":0.2139354556320936,"score_spread":0.2050401543728373,"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."}}