{"id":"W2166665348","doi":"10.1109/psce.2006.296400","title":"Analysis of Market Power Using an AC Transmission System","year":2006,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Oligopoly; AC power; Node (physics); Competition (biology); Electric power system; Computer science; Operator (biology); Market power; Transmission (telecommunications); Set (abstract data type); Power flow; Transmission network; Nonlinear system; Mathematical optimization; Power (physics); Power-flow study; Transmission system; Electric power transmission; Voltage; Engineering; Mathematical economics; Economics; Microeconomics; Electrical engineering; Mathematics; Telecommunications; Cournot competition","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":[0.0004067229,0.0005094283,0.0004354493,0.0004872188,0.0004736331,0.001408074,0.0005970562,0.0008271351,0.006581623],"category_scores_gemma":[0.0014898,0.0002838181,0.0002983758,0.000904056,0.0007003119,0.001209564,0.0004407512,0.0004740676,0.0002650981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017963,"about_ca_system_score_gemma":0.0005434427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01478848,"about_ca_topic_score_gemma":0.007951701,"domain_scores_codex":[0.9997863,0.0001017614,0.000006724449,0.00002653025,0.00005476198,0.00002406118],"domain_scores_gemma":[0.9995649,0.0002664357,0.00005885268,0.00001460916,0.00007424685,0.00002094956],"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":[0.00003342449,0.00001828321,0.0003921293,0.00004309948,0.00001433564,0.0002245518,0.00003633305,0.9672382,0.0007666957,0.02762956,0.0004557531,0.003147625],"study_design_scores_gemma":[0.000005197087,0.00001266655,0.0001603793,0.000002374907,0.000003407852,0.00001468719,0.00001618327,0.9967662,0.00005613609,0.002687922,0.0002722787,0.000002649183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5111181,0.001375261,0.3495496,0.001623592,0.00009025266,0.0001561569,0.0006421175,0.0003576612,0.1350874],"genre_scores_gemma":[0.9896908,0.0002727546,0.004165142,0.00002495709,0.00002613561,0.00003365111,0.00004061101,0.0000253972,0.005720518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01478848,"threshold_uncertainty_score":0.02940482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004967826262790539,"score_gpt":0.1932419603239102,"score_spread":0.1882741340611196,"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."}}