{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001201917,0.000211531,0.0002742966,0.00008871621,0.00004025096,0.0001152027,0.0001783865,0.0001432891,0.0005796666],"category_scores_gemma":[0.000004160357,0.0002438295,0.00006705481,0.00013715,0.000006931095,0.00004608071,0.000278749,0.0003368552,0.000008796333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003891746,"about_ca_system_score_gemma":0.00006063965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005730183,"about_ca_topic_score_gemma":0.0003208187,"domain_scores_codex":[0.9990487,0.00005030941,0.0003055303,0.0002058478,0.0001788776,0.0002107529],"domain_scores_gemma":[0.9993868,0.00001975501,0.00004258252,0.0004298055,0.00006673072,0.00005435996],"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":[5.968957e-7,0.00002493625,0.001474248,0.0003287453,0.0002070865,0.000009707567,0.0001670436,0.995437,0.0002653921,0.0001892163,0.001567123,0.0003289231],"study_design_scores_gemma":[0.0001597598,0.000005349154,0.0003075744,0.0001325245,0.00005508749,0.000007750034,0.00009741988,0.995188,0.002037014,0.00004654603,0.001638551,0.0003243987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08591323,0.000933325,0.8852224,0.00003226033,0.002034924,0.0005710626,0.00002641543,0.000748459,0.02451787],"genre_scores_gemma":[0.9502709,0.00006116675,0.04890381,0.00004668721,0.00007630249,0.00002243547,0.000443953,0.00005062241,0.0001241117],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8643577,"threshold_uncertainty_score":0.9943081,"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."}}