{"id":"W2130102883","doi":"10.1109/tpwrd.2009.2033929","title":"Heuristic Determination of Distribution Trees","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Simulated annealing; Tabu search; Mathematical optimization; Heuristic; Topology (electrical circuits); Network topology; Computer science; Hill climbing; 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":[0.001040726,0.0005413879,0.0008524688,0.001650686,0.0008377259,0.001031194,0.0007256683,0.0007705498,0.003629209],"category_scores_gemma":[0.006101999,0.0006020628,0.0005937152,0.001178059,0.0007337806,0.000964663,0.0007843303,0.0006773782,0.0003985163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001347896,"about_ca_system_score_gemma":0.001562103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004842431,"about_ca_topic_score_gemma":0.005978405,"domain_scores_codex":[0.9993309,0.0003517872,0.00002293208,0.00007247365,0.0001147451,0.0001072441],"domain_scores_gemma":[0.9981195,0.001370828,0.0001261692,0.0001029555,0.0002165359,0.0000639873],"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":[0.00008125144,0.00005283744,0.001524133,0.00008123176,0.00002460471,0.0001132343,0.0001961454,0.9163076,0.001241162,0.01955355,0.002090316,0.05873391],"study_design_scores_gemma":[0.00003732946,0.0000288113,0.000315219,0.00002030574,0.00001403418,0.00004903398,0.00009585056,0.9859477,0.0006760504,0.01075858,0.002049584,0.000007413056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.202623,0.0006122519,0.7767681,0.0003354794,0.00004856048,0.0003499076,0.000321568,0.0006960709,0.01824503],"genre_scores_gemma":[0.6677424,0.0002539598,0.3289239,0.00008380869,0.00001641164,0.0003249547,0.0003713359,0.0001649283,0.002118343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004842431,"threshold_uncertainty_score":0.01214093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005392393408888621,"score_gpt":0.2019614438086904,"score_spread":0.1965690503998018,"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."}}