{"id":"W3101913426","doi":"","title":"A comparison of partitioning strategies in AC optimal power flow","year":2019,"lang":"en","type":"article","venue":"IEEE PES Innovative Smart Grid Technologies Conference","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Partition (number theory); Scalability; Benchmark (surveying); Computer science; Power flow; Mathematical optimization; Grid; Spectral clustering; Graph partition; Cluster analysis; Parallel computing; Power (physics); Algorithm; Electric power system; Graph; Mathematics; Theoretical computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001611014,0.0002689874,0.0004743753,0.000340677,0.00003243304,0.00006325432,0.0004207132,0.0002430899,0.0001015033],"category_scores_gemma":[0.00009441234,0.0002791853,0.00003920276,0.001350709,0.0002924946,0.0005107087,0.000104593,0.0005842519,0.000069039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001203504,"about_ca_system_score_gemma":0.0000795584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001145131,"about_ca_topic_score_gemma":0.00002401637,"domain_scores_codex":[0.9984916,0.00002086822,0.0005691931,0.0002987066,0.0002122894,0.0004073262],"domain_scores_gemma":[0.9990381,0.00007093534,0.000129412,0.0003849384,0.0003607177,0.00001591505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001366944,0.0003535435,0.2773416,0.0004665481,0.000224432,0.00002096268,0.00210852,0.2660105,0.3388264,0.09554122,0.003887181,0.01508239],"study_design_scores_gemma":[0.001211872,0.0008515644,0.04252612,0.0006075927,0.00001451821,0.000007325305,0.02010859,0.1960383,0.7321085,0.002687752,0.00270631,0.001131566],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9554657,0.0001667262,0.03592982,0.0001066693,0.0008372115,0.0003232056,0.0001072176,0.001030755,0.006032705],"genre_scores_gemma":[0.994613,0.00002415965,0.005207304,0.000004507182,0.00001161987,0.00005562029,0.00005425691,0.00001994912,0.000009570548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3932821,"threshold_uncertainty_score":0.999966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02125913625258257,"score_gpt":0.2796835700562902,"score_spread":0.2584244338037076,"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."}}