{"id":"W4252268603","doi":"10.32920/ryerson.14648058","title":"Unit commitment using complementarity","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"","keywords":"Mathematical optimization; Power system simulation; Complementarity (molecular biology); Computer science; Nonlinear system; Complementarity theory; Economic dispatch; Linear programming; Generator (circuit theory); Integer programming; Grid; Integer (computer science); Power (physics); Mathematics; Electric power system","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":[0.001015659,0.001165115,0.0009841289,0.0007903181,0.0005301456,0.001921228,0.001027638,0.0007928768,0.01169134],"category_scores_gemma":[0.00264992,0.0004915131,0.0008706531,0.001987132,0.001168829,0.001337338,0.001859461,0.001740791,0.002014492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00119201,"about_ca_system_score_gemma":0.001487641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004033876,"about_ca_topic_score_gemma":0.002996288,"domain_scores_codex":[0.9988763,0.0004605315,0.0000365354,0.0001336694,0.0004058335,0.00008710541],"domain_scores_gemma":[0.9992883,0.0004251399,0.00007037618,0.00006975637,0.0001194631,0.00002701684],"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":[0.0000301691,0.00001991954,0.0001163268,0.0002343153,0.00005460189,0.00008384662,0.00005531142,0.506514,0.001134407,0.4437859,0.005412433,0.04255866],"study_design_scores_gemma":[0.00002008142,0.0000420534,0.00007662726,0.0000778094,0.00001564446,0.00007587839,0.00002548839,0.7310452,0.0008251271,0.2523778,0.01539769,0.00002045469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00179854,0.001037736,0.9525275,0.0003691425,0.00013297,0.00006581549,0.0001116708,0.0001316228,0.04382505],"genre_scores_gemma":[0.5147846,0.005029238,0.4411613,0.000821523,0.0004092742,0.0007868627,0.000544968,0.0003904637,0.03607191],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01169134,"threshold_uncertainty_score":0.03911138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05794564141867547,"score_gpt":0.2770386808553337,"score_spread":0.2190930394366582,"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."}}