{"id":"W4366977557","doi":"10.1016/j.renene.2023.04.113","title":"Design of optimal operating rule curves for hydropower multi-reservoir systems by an influential optimization method","year":2023,"lang":"en","type":"article","venue":"Renewable Energy","topic":"Water resources management and optimization","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"","keywords":"Particle swarm optimization; Hydropower; Differential evolution; Benchmark (surveying); Mathematical optimization; Renewable energy; Computer science; Convergence (economics); Engineering; Mathematics","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":[0.000360762,0.000164443,0.0002214405,0.0001590734,0.00008484704,0.00008219833,0.0001916251,0.00008366449,0.00002239742],"category_scores_gemma":[0.00002578673,0.0001676785,0.00004186161,0.0003509956,0.00001205268,0.0003466377,0.00004643999,0.00003056526,0.000001550673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003142102,"about_ca_system_score_gemma":0.000009131425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009347547,"about_ca_topic_score_gemma":0.00001058753,"domain_scores_codex":[0.998935,0.00009619367,0.0003250285,0.0002111178,0.0001622118,0.000270476],"domain_scores_gemma":[0.9995467,0.00005125387,0.00006754865,0.0002027664,0.00007341601,0.00005832869],"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":[0.00001011125,0.00002097562,0.00001082404,0.0002472806,0.00005500728,6.748894e-7,0.00008384855,0.985126,0.01028312,0.00001020998,0.004057602,0.00009429945],"study_design_scores_gemma":[0.0004831816,0.0000538835,0.000001141281,0.00008831343,0.00002995454,4.179306e-7,0.00005677163,0.9677863,0.02951522,0.000003577398,0.001797922,0.0001833388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001864688,0.0005433552,0.9965145,0.000008840275,0.000213314,0.0002809016,0.00001786902,0.0003811229,0.0001754385],"genre_scores_gemma":[0.111874,0.001583237,0.8704315,0.00006885224,0.000335169,0.0006580633,0.003091106,0.0003422354,0.01161575],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1260829,"threshold_uncertainty_score":0.6837731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02131992731416031,"score_gpt":0.2541329518564404,"score_spread":0.2328130245422801,"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."}}