{"id":"W2773893359","doi":"10.1109/isgt-la.2017.8126715","title":"Optimal location and size for various renewable distributed generators in distribution networks","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Solver; Node (physics); Distributed generation; Computer science; Variable (mathematics); AC power; Voltage; Renewable energy; Genetic algorithm; Power (physics); Mathematical optimization; Engineering; Electrical engineering; Mathematics","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":[0.0001975425,0.000159188,0.0001663691,0.00001421395,0.0002164414,0.0002017295,0.000138621,0.0001496225,0.00001010913],"category_scores_gemma":[0.0002235709,0.0001705827,0.00002962423,0.0000877013,0.00004852714,0.0003380564,0.00004273884,0.0000960514,0.000002742891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001904738,"about_ca_system_score_gemma":0.00001699189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001872723,"about_ca_topic_score_gemma":0.0002364234,"domain_scores_codex":[0.9991537,0.00001011018,0.000224884,0.0002127592,0.00007471794,0.0003238786],"domain_scores_gemma":[0.9994262,0.00005691031,0.00004884645,0.0003079671,0.0000778531,0.00008223489],"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":[0.00003879576,0.00003060016,0.003393501,0.00004882315,0.00002061258,0.000002403491,0.00001439358,0.9861785,0.0006380286,0.001087456,0.00700924,0.001537626],"study_design_scores_gemma":[0.0007931531,0.00004834113,0.04570711,0.00002264737,0.00001681427,0.000003193529,0.00001521777,0.9487276,0.002374307,0.0001280265,0.001933688,0.0002299246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2288787,0.0001359916,0.769751,0.0000900231,0.0002802314,0.000297762,0.0002607993,0.0001481849,0.0001573538],"genre_scores_gemma":[0.9962194,0.00005423739,0.002340692,0.000008303934,0.0001014141,0.00007192184,0.001143985,0.00002025254,0.00003977482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7674103,"threshold_uncertainty_score":0.6956159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006956205150447779,"score_gpt":0.2189297136923709,"score_spread":0.2119735085419231,"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."}}