{"id":"W2142713059","doi":"10.1109/pesw.2000.850064","title":"Generator contribution coefficients for pricing transmission services","year":2002,"lang":"en","type":"article","venue":"2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.00CH37077)","topic":"Electric Power System Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Government of Newfoundland and Labrador","funders":"","keywords":"Generator (circuit theory); Electric power transmission; Computer science; Slack bus; Electric power system; Transmission (telecommunications); Tariff; Flow (mathematics); Power flow; Transmission line; Transmission system; Power-flow study; Mathematical optimization; Power (physics); AC power; Electrical engineering; Telecommunications; Mathematics; Voltage; Engineering; Economics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005334875,0.0007692911,0.0006666897,0.0001993847,0.0002550787,0.000409204,0.0006036662,0.0004756776,0.00008456708],"category_scores_gemma":[0.00007726563,0.0008306163,0.0003836556,0.0006851074,0.00004243387,0.0007054603,0.00004332982,0.0003574997,0.00009387109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006810971,"about_ca_system_score_gemma":0.00004111832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009540527,"about_ca_topic_score_gemma":7.543708e-7,"domain_scores_codex":[0.9965021,0.00001289745,0.0009043991,0.0007850598,0.0005624996,0.001233036],"domain_scores_gemma":[0.9981,0.00009483898,0.0002127938,0.0002578914,0.001014244,0.0003202543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005431085,0.0002172839,0.0007796792,0.002805616,0.0005183436,0.00000300425,0.01973142,0.09131587,0.8601126,0.0001364503,0.02231313,0.002012294],"study_design_scores_gemma":[0.00109069,0.0001401329,0.00004334647,0.0009422063,0.00008574966,0.00001515071,0.0002724362,0.9488118,0.04023275,0.000005980481,0.007499983,0.0008597912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3437667,0.0006195672,0.6460934,0.0001673847,0.002459279,0.001754706,0.00005639881,0.00259389,0.002488643],"genre_scores_gemma":[0.9640992,0.0002967329,0.03398216,0.0001382814,0.0004246653,0.0002769604,0.0000493029,0.0002281919,0.0005044829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8574959,"threshold_uncertainty_score":0.9994144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006112609138245592,"score_gpt":0.1853616185557154,"score_spread":0.1792490094174698,"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."}}