{"id":"W4410614224","doi":"10.1109/oajpe.2025.3572718","title":"Data Driven Reduced Pi-Model of Feeders for Distribution Network Representation With DERs for Fast Reconfiguration","year":2025,"lang":"en","type":"article","venue":"IEEE Open Access Journal of Power and Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control reconfiguration; Representation (politics); Distribution (mathematics); Pi; Computer science; Mathematics; Embedded system; Mathematical analysis; Political science; Geometry","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":[0.0001729648,0.0006087465,0.0004470989,0.0002938843,0.0002258892,0.0006049552,0.000678691,0.000381579,0.005343712],"category_scores_gemma":[0.0006337941,0.000318258,0.0006630761,0.0003966693,0.000178078,0.0006654258,0.0002946176,0.001121003,0.001136376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005250446,"about_ca_system_score_gemma":0.0006484808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009111075,"about_ca_topic_score_gemma":0.01102477,"domain_scores_codex":[0.9999105,0.00002654,0.0000039469,0.00001814781,0.00003100994,0.000009889468],"domain_scores_gemma":[0.9998453,0.00006347237,0.00001796991,0.00002627541,0.00004060667,0.000006272221],"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":[0.00001921896,0.00001212186,0.0001827068,0.00001729356,0.000008519542,0.00002924154,0.00001308312,0.9836566,0.0009747607,0.001824836,0.0004647643,0.01279687],"study_design_scores_gemma":[0.000001751913,0.000005439653,0.00003458697,0.00000119531,0.000001682406,0.000004863692,0.000003094636,0.9985595,0.0002168194,0.0006165987,0.0005533175,0.000001154332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01782805,0.00004931284,0.9757214,0.00009476226,0.00002533645,0.00005184894,0.0003040938,0.001127784,0.004797452],"genre_scores_gemma":[0.6696523,0.000234903,0.3163324,0.00007927586,0.00002948304,0.0003279572,0.001712895,0.0002825958,0.01134815],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009111075,"threshold_uncertainty_score":0.01811612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05584790966201754,"score_gpt":0.3521594307823991,"score_spread":0.2963115211203816,"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."}}