{"id":"W4205735987","doi":"10.1007/s11269-021-03034-8","title":"Optimal Operational Scheduling of Pumps to Improve the Performance of Water Distribution Networks","year":2022,"lang":"en","type":"article","venue":"Water Resources Management","topic":"Water Systems and Optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Jacobs (Canada)","funders":"","keywords":"Particle swarm optimization; MATLAB; Reliability engineering; Computer science; Reliability (semiconductor); Software; Leakage (economics); Scheduling (production processes); Simulation; Real-time computing; Power (physics); Engineering; Algorithm","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":[0.0003063219,0.00008944458,0.0001042801,0.0000471208,0.000137949,0.00002842592,0.000196762,0.00001586988,0.00007289323],"category_scores_gemma":[4.369429e-7,0.00005185317,0.00003583506,0.0000753643,0.00001395325,0.00006296214,0.0002712286,0.00007271248,0.000005565327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004763114,"about_ca_system_score_gemma":6.809728e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000195179,"about_ca_topic_score_gemma":0.000001503096,"domain_scores_codex":[0.999188,0.00002783369,0.0002644604,0.0001153282,0.0002149743,0.0001893887],"domain_scores_gemma":[0.9997472,0.000003089966,0.00002106885,0.0001829499,0.00002471111,0.00002101625],"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":[0.00002023815,0.00001213791,0.0001766551,0.00008862076,0.00004844651,6.697516e-7,0.001491548,0.9965262,0.001092016,0.00005552574,0.0002177843,0.0002701854],"study_design_scores_gemma":[0.0001928691,0.00008594301,0.0004260891,0.0000163561,0.00002033752,0.000001159528,0.0002685703,0.9301304,0.03746043,0.000001638519,0.03129593,0.0001003311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9613622,0.00003092834,0.03742996,0.0001219958,0.0002559839,0.0003520534,0.00001425651,0.00003339886,0.0003991787],"genre_scores_gemma":[0.9984246,0.000005455469,0.0004721851,0.0000219902,0.00006363588,0.0001195433,0.000143397,0.00001453329,0.000734675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06639583,"threshold_uncertainty_score":0.2114511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00412070599879554,"score_gpt":0.1656542126263071,"score_spread":0.1615335066275115,"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."}}