{"id":"W4404708495","doi":"10.1109/access.2024.3505258","title":"Novel Time-Varying Risk-Averse and Risk-Seeker Frameworks for Uncertain Wind Energy Generation in Electric Power Systems","year":2024,"lang":"en","type":"article","venue":"IEEE Access","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Research and Innovation","keywords":"Wind power; Electric power system; Computer science; Electricity generation; Energy (signal processing); Risk analysis (engineering); Power (physics); Electrical engineering; Business; Engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002649614,0.0002031268,0.0001999124,0.0002619208,0.00009418592,0.0003882982,0.0001442535,0.0002858682,0.00001650815],"category_scores_gemma":[0.00004893359,0.0001999613,0.00005088143,0.0004417347,0.00001115023,0.0004519587,0.00002107837,0.0004052603,0.00000567315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009360359,"about_ca_system_score_gemma":0.00002368778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007677748,"about_ca_topic_score_gemma":0.000109488,"domain_scores_codex":[0.998943,0.00003213433,0.0002764369,0.0002956823,0.0001213273,0.0003314198],"domain_scores_gemma":[0.9994732,0.0002319362,0.00004956842,0.0001498743,0.00003077053,0.0000647077],"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":[0.00001023386,0.00001244896,0.0008274273,0.0000986812,0.00008582479,0.00001071567,0.0002482086,0.9794312,0.01171084,0.0003122609,0.001587334,0.005664797],"study_design_scores_gemma":[0.0002664563,0.00002412367,0.000153484,0.0001501678,0.00003767316,0.00001157025,0.000008581144,0.9899954,0.003880327,0.0001056142,0.005110612,0.0002560429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.719843,0.004649113,0.2721763,0.0000105286,0.001963613,0.0001799215,0.00004803172,0.0002609376,0.0008686371],"genre_scores_gemma":[0.99823,0.0005065438,0.0004902269,0.0000258328,0.0004449076,0.00004620914,0.00002835532,0.00006657862,0.0001613213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2783871,"threshold_uncertainty_score":0.8154185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655598056399141,"score_gpt":0.2485755920887707,"score_spread":0.2320196115247793,"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."}}