{"id":"W2083053088","doi":"10.1109/naps.2008.5307307","title":"The role of distributed generation in restructured power systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Software deployment; Distributed generation; Distributed power generation; Electricity; Electric power system; Computer science; Electricity generation; Electricity market; Penetration (warfare); Distributed computing; Power (physics); Risk analysis (engineering); Business; Operations research; Electrical engineering; Engineering; Renewable energy; Software engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00006346701,0.00006334447,0.00007770024,0.0000214156,0.00003919422,0.00001139055,0.00007043201,0.00004998794,0.000009432847],"category_scores_gemma":[0.00002285846,0.00004679163,0.00001948418,0.000142281,0.00002433321,0.0000635238,0.000008598191,0.00006229503,0.00000711498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000634959,"about_ca_system_score_gemma":0.000008792578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004918106,"about_ca_topic_score_gemma":0.00002919163,"domain_scores_codex":[0.9995114,0.00001601214,0.0001905462,0.00006154751,0.0000992803,0.000121273],"domain_scores_gemma":[0.9997686,0.00001549954,0.00001741328,0.0001442337,0.00003406722,0.0000201635],"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":[0.0000306512,0.0000362091,0.0115298,0.00002358203,0.00005043727,0.00001020838,0.0003319224,0.7326167,0.2156686,0.02300036,0.01617244,0.0005291693],"study_design_scores_gemma":[0.0004055367,0.00004457723,0.04984307,0.00001039034,0.000005021509,0.00002527429,0.0002489979,0.868229,0.06335014,0.0001511649,0.01747964,0.0002071476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891028,0.0008337141,0.006734081,0.00001643939,0.0002833559,0.000140606,0.00005743634,0.00008555112,0.002745967],"genre_scores_gemma":[0.999737,0.00003392233,0.00006480669,0.000001120712,0.00001782645,0.000008027597,0.0001090139,0.000007343747,0.00002098677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1523184,"threshold_uncertainty_score":0.1908107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006312224105489064,"score_gpt":0.1825054578651385,"score_spread":0.1761932337596494,"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."}}