{"id":"W2067967009","doi":"10.1016/j.ijpe.2010.10.007","title":"Financial and operational decisions in the electricity sector: Contract portfolio optimization with the conditional value-at-risk criterion","year":2010,"lang":"en","type":"article","venue":"International Journal of Production Economics","topic":"Electric Power System Optimization","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; University of New Brunswick; University of Toronto","funders":"","keywords":"CVAR; Expected shortfall; Forward contract; Stochastic programming; Procurement; Portfolio; Hedge; Value at risk; Portfolio optimization; Risk management; Volatility (finance); Electricity; Robust optimization; Microeconomics; Computer science; Economics; Business; Mathematical optimization; Actuarial science; Finance; Futures contract","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":[0.001052947,0.0001186984,0.0001306689,0.0002306443,0.0001306323,0.0001342515,0.0002602751,0.00006878597,0.00005820202],"category_scores_gemma":[0.0004096079,0.00008019998,0.00004242006,0.0001429887,0.00005486178,0.0005824397,0.00001475341,0.0004283696,0.000002134069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000189133,"about_ca_system_score_gemma":0.0001226136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001393785,"about_ca_topic_score_gemma":0.0001977633,"domain_scores_codex":[0.9989823,0.00007853356,0.0004529392,0.000134809,0.0002365058,0.0001148739],"domain_scores_gemma":[0.9990026,0.0002023946,0.0002970102,0.0001149415,0.0003536139,0.00002938482],"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":[0.0001000752,0.00004368411,0.004599439,0.000001411115,0.00006353273,0.000004720973,0.000303105,0.988299,0.0007956117,0.00252761,0.001645494,0.00161633],"study_design_scores_gemma":[0.002336131,0.0002410526,0.1306271,0.00004713426,0.0001000403,0.005821147,0.0001256608,0.8397385,0.003702716,0.002436909,0.01437152,0.000451995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9131538,0.0001133008,0.08222976,0.002281672,0.001770189,0.0002112337,0.00002489316,0.00001476434,0.0002004001],"genre_scores_gemma":[0.9958133,0.0005765842,0.002437625,0.0001797202,0.0009109206,0.00001237113,0.00003357801,0.00001511924,0.00002083997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1485604,"threshold_uncertainty_score":0.327046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005308610124878929,"score_gpt":0.2058521125812041,"score_spread":0.2005435024563251,"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."}}