{"id":"W4411570120","doi":"10.2316/j.2025.203-0559","title":"PLANNING AND FAULT CONTROL OF URBAN DISTRIBUTION LINES THROUGH OPTIMAL DESIGN, 19-25.","year":2025,"lang":"en","type":"article","venue":"International Journal of Power and Energy Systems","topic":"Power Systems and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Fault (geology); Control (management); Distribution (mathematics); Reliability engineering; Computer science; Environmental science; Operations research; Engineering; Mathematics; Geology; Artificial intelligence; Seismology; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001715035,0.00009922824,0.0002375551,0.00011661,0.00002287419,0.00005422294,0.0001468132,0.00008351792,0.000001371609],"category_scores_gemma":[0.00005166441,0.00008006991,0.00004438042,0.00005579692,0.00004162894,0.0001645453,0.00002382105,0.00008402798,1.188985e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004146077,"about_ca_system_score_gemma":0.00001875254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007646334,"about_ca_topic_score_gemma":8.743276e-7,"domain_scores_codex":[0.9992307,0.00002354976,0.0004214559,0.00006830002,0.0001651689,0.00009086106],"domain_scores_gemma":[0.9994963,0.00008836116,0.0001426306,0.00005571408,0.0001882955,0.00002868848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007215355,0.0001999511,0.04528886,0.000602215,0.006647228,0.0004845322,0.003712754,0.6276109,0.02737556,0.2143921,0.06237598,0.01058832],"study_design_scores_gemma":[0.008106574,0.0008010655,0.01249531,0.004791788,0.0002531838,0.001968871,0.004979427,0.2268999,0.01645497,0.001965161,0.7203734,0.0009103838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05492778,0.02279991,0.9186384,0.0001279733,0.002575167,0.00003211746,0.00003866667,0.00004315311,0.0008168455],"genre_scores_gemma":[0.9993262,0.0002345426,0.0001973352,0.0000137567,0.0001111026,0.000003234813,0.000003274633,0.000006042248,0.0001045251],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9443984,"threshold_uncertainty_score":0.3265156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00897372474189462,"score_gpt":0.2377014983667083,"score_spread":0.2287277736248137,"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."}}