{"id":"W2979853567","doi":"10.1049/iet-gtd.2019.0726","title":"Rectangular branch‐based load flow","year":2019,"lang":"en","type":"article","venue":"IET Generation Transmission & Distribution","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flow (mathematics); Computer science; Mechanics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002859385,0.000649182,0.0005728896,0.0005707339,0.0003232102,0.000910583,0.0008396936,0.0003598268,0.02092097],"category_scores_gemma":[0.0009433783,0.0003579929,0.0005171421,0.0009807677,0.0003273714,0.001089203,0.0007345214,0.0006640668,0.003172211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004476915,"about_ca_system_score_gemma":0.0007525528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004287955,"about_ca_topic_score_gemma":0.004793236,"domain_scores_codex":[0.9997751,0.00004640016,0.00001285431,0.00006842743,0.0000749715,0.0000222085],"domain_scores_gemma":[0.9998031,0.00005659072,0.00002354344,0.00003587396,0.00007004741,0.00001070285],"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":[0.0001072998,0.00005133741,0.0009858242,0.000124592,0.00002570039,0.00007967075,0.0001484956,0.6457839,0.008466439,0.04167047,0.005932554,0.2966238],"study_design_scores_gemma":[0.00001326482,0.00002563092,0.0001250637,0.000006342681,0.000004433897,0.00001675516,0.00001580482,0.986955,0.001228316,0.006912076,0.00469132,0.000005972312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006326866,0.00004560018,0.9852629,0.00005166699,0.00002684792,0.00007897089,0.0001663669,0.0005958691,0.007444991],"genre_scores_gemma":[0.4064409,0.0003126331,0.5614533,0.00009777836,0.0000580967,0.0003319913,0.001157651,0.0004055507,0.02974212],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02092097,"threshold_uncertainty_score":0.0699876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007495624646409158,"score_gpt":0.2006610273813019,"score_spread":0.1931654027348927,"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."}}