{"id":"W2024587919","doi":"10.1109/pes.2010.5589559","title":"Unit commitment with wind generation accounting for transmission congestion","year":2010,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Residual; Power system simulation; Mathematical optimization; Set (abstract data type); Schedule; Transmission (telecommunications); Computer science; Wind power; Upper and lower bounds; Power (physics); Electric power system; Engineering; Mathematics; Algorithm; Telecommunications; Electrical 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":[0.0001255597,0.00008452249,0.00007137519,0.00005340957,0.00006508675,0.00004206325,0.00004355791,0.00006833181,0.00004171487],"category_scores_gemma":[0.000005851027,0.00006950912,0.00001331408,0.0001050786,0.000005283675,0.0001614802,0.000001667355,0.00007990812,0.000004293414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002085264,"about_ca_system_score_gemma":0.0000124561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005349721,"about_ca_topic_score_gemma":0.00005075241,"domain_scores_codex":[0.9995763,0.00000655604,0.0001200476,0.00009133144,0.00008585057,0.0001199282],"domain_scores_gemma":[0.9997598,0.00002424234,0.00001985431,0.00009661731,0.00006667708,0.0000328293],"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":[0.00002798357,0.00004299623,0.002085323,0.0001385104,0.00006348172,8.994164e-7,0.0003456923,0.4727002,0.4700898,0.00343527,0.002916817,0.04815301],"study_design_scores_gemma":[0.0005424327,0.00005757264,0.000521045,0.00001471186,0.00001875282,0.000006927084,0.00001086854,0.935697,0.05286653,0.00001319154,0.01011279,0.0001382438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1914529,0.00002513379,0.8047593,0.00007597557,0.0002514541,0.0004145011,0.000001296825,0.0002462354,0.002773282],"genre_scores_gemma":[0.9677129,0.000005005912,0.03180988,0.00001839698,0.0001178417,0.00003021933,0.00005527593,0.00002508092,0.000225338],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7762601,"threshold_uncertainty_score":0.28345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01169954836860633,"score_gpt":0.2116037028870523,"score_spread":0.199904154518446,"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."}}