{"id":"W2160808904","doi":"10.1109/pes.2003.1270386","title":"Closed-form solution to calculate generator contributions to loads and line flows in an open access market","year":2004,"lang":"en","type":"article","venue":"2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491)","topic":"Electric Power System Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Tracing; Computation; Computer science; Generator (circuit theory); Electric power transmission; Mathematical optimization; Electric power system; Linear programming; Transmission line; Transmission (telecommunications); Line (geometry); Power (physics); Telecommunications; Electrical engineering; Mathematics; Engineering; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002629318,0.0009742391,0.001023155,0.001005833,0.0006461245,0.001855489,0.001211658,0.001995513,0.00842425],"category_scores_gemma":[0.009436133,0.0006935433,0.0005112313,0.001065069,0.0009539751,0.001742015,0.001028495,0.001353161,0.001237207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001172781,"about_ca_system_score_gemma":0.002366118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005672506,"about_ca_topic_score_gemma":0.009107945,"domain_scores_codex":[0.9994686,0.0001812574,0.000020626,0.00006712059,0.0001925126,0.00006984391],"domain_scores_gemma":[0.9962985,0.002738504,0.0001865684,0.0001225064,0.0005721394,0.00008181925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003031793,0.00006802507,0.0002956938,0.0000642378,0.00001277891,0.00008197435,0.00005834268,0.9446158,0.0006140574,0.02990255,0.001633101,0.02262316],"study_design_scores_gemma":[0.00001057774,0.000009750783,0.00004876061,0.000004891998,0.000002696022,0.0000141189,0.00001624834,0.9903266,0.0002025644,0.008835269,0.0005252418,0.000003250693],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.012145,0.0001457109,0.9817058,0.0002131755,0.00003960485,0.00006951755,0.00008264535,0.0002957861,0.005302839],"genre_scores_gemma":[0.4802041,0.0005059695,0.5000849,0.000234345,0.0001163877,0.0005945452,0.0003593253,0.0003877948,0.01751264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00842425,"threshold_uncertainty_score":0.02818191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01174616760905839,"score_gpt":0.2805061016743096,"score_spread":0.2687599340652512,"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."}}