{"id":"W4414008470","doi":"10.1016/j.asoc.2025.113846","title":"An efficient mathematical-based optimization method to optimize multi-hydropower operating rules","year":2025,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Water Systems and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island","funders":"King Fahd University of Petroleum and Minerals","keywords":"Computer science; Hydropower; Mathematical optimization; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001110306,0.0008021853,0.001345939,0.0008367004,0.0005578607,0.001198843,0.001235699,0.001197603,0.004639958],"category_scores_gemma":[0.002345873,0.0006854675,0.001062138,0.0009796134,0.0005573409,0.0007929617,0.0008825332,0.001390686,0.0008614222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006997605,"about_ca_system_score_gemma":0.001840285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005227951,"about_ca_topic_score_gemma":0.006423003,"domain_scores_codex":[0.9996462,0.00009434269,0.00002040732,0.00004266071,0.0001600122,0.00003635837],"domain_scores_gemma":[0.9991859,0.000489699,0.00004642481,0.00004513383,0.000199814,0.00003299058],"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":[0.00002493233,0.00005173617,0.0001258071,0.00007366296,0.00003211404,0.00003119875,0.00001850862,0.9497299,0.00102564,0.009559585,0.001122499,0.03820439],"study_design_scores_gemma":[0.000003809834,0.000005045242,0.00001394566,0.000003115866,0.000002338995,0.000003855692,0.000001412087,0.998811,0.0001191732,0.0007173532,0.0003173403,0.000001499495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003922568,0.0001584899,0.9911957,0.0001118307,0.00008643843,0.00005654824,0.00005036844,0.0002636554,0.004154388],"genre_scores_gemma":[0.210253,0.0003019686,0.781705,0.0002191494,0.0001217316,0.0005161297,0.0002177852,0.000348715,0.006316553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005227951,"threshold_uncertainty_score":0.01552218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008191508408626398,"score_gpt":0.2620007916477389,"score_spread":0.2538092832391125,"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."}}