{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007117494,0.0008317754,0.001105212,0.0003521242,0.0001793558,0.0001644562,0.0004621746,0.00056617,0.00003320817],"category_scores_gemma":[0.000331367,0.0009455609,0.0007658405,0.003730733,0.0000781639,0.0003225273,0.00003982058,0.000594387,0.00006750561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001490809,"about_ca_system_score_gemma":0.0001530785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009987147,"about_ca_topic_score_gemma":0.000005781301,"domain_scores_codex":[0.9957841,0.00006701075,0.001235421,0.0007709708,0.0008806782,0.001261811],"domain_scores_gemma":[0.9976988,0.00009796664,0.0002251654,0.0007557236,0.000839729,0.0003825545],"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":[0.000006744684,0.00007063166,0.00004726886,0.00006785818,0.001141446,0.000005125819,0.0002509752,0.718747,0.2743319,0.0001000285,0.005211314,0.0000197603],"study_design_scores_gemma":[0.000765448,0.0001258806,0.0003488994,0.00009944438,0.0007294344,0.00001259912,0.0000342665,0.9740669,0.02253509,0.000002343718,0.0003628365,0.0009168789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4900469,0.0004191947,0.5041889,0.00001748148,0.00375841,0.0003813262,0.0004836629,0.0006448503,0.00005930283],"genre_scores_gemma":[0.9706896,0.00007193389,0.02722433,0.00004034703,0.0006365597,0.0001096616,0.0009738367,0.0001894917,0.00006424274],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4806427,"threshold_uncertainty_score":0.9992995,"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."}}