{"id":"W2130462936","doi":"10.1109/pes.2003.1270485","title":"Stochastic power flow analysis of electrical distributed generation systems","year":2004,"lang":"en","type":"article","venue":"2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491)","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Power flow; Computer science; Flow (mathematics); Electric power system; Power (physics); Mechanics; Physics","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":[0.000949317,0.0003810185,0.0004895712,0.000571124,0.0002733448,0.0006390772,0.0003551018,0.0004222617,0.0008164486],"category_scores_gemma":[0.002736597,0.0003329523,0.0003103909,0.0004633927,0.0007674061,0.0007749972,0.0003467724,0.0004301155,0.00007818436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000937872,"about_ca_system_score_gemma":0.0008948808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004353271,"about_ca_topic_score_gemma":0.002231565,"domain_scores_codex":[0.9995769,0.000186829,0.00001055203,0.00004908398,0.0001407676,0.00003589828],"domain_scores_gemma":[0.9992241,0.0004942407,0.000101904,0.0000291719,0.0001286696,0.00002207018],"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":[0.000005525349,0.000003515275,0.0001070546,0.000004760437,0.000003743972,0.000007881705,0.000004296581,0.9897842,0.0001487912,0.008193992,0.00005761544,0.001678595],"study_design_scores_gemma":[0.000001416122,0.000001873733,0.00003682323,8.3803e-7,4.751974e-7,0.000001967449,7.478464e-7,0.9971417,0.00003786011,0.002712925,0.00006254244,8.647672e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03114045,0.0002418734,0.9662936,0.000149937,0.00001617283,0.00002931387,0.00004515866,0.00008465716,0.001998815],"genre_scores_gemma":[0.9364833,0.0004399494,0.06080041,0.00004357759,0.00005410621,0.0001134998,0.0001514625,0.00003883301,0.001874893],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004353271,"threshold_uncertainty_score":0.008655906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006865075431896715,"score_gpt":0.2033750927129286,"score_spread":0.1965100172810319,"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."}}