{"id":"W2794439414","doi":"10.1007/s11269-018-1961-1","title":"Method for Extended Period Simulation of Water Distribution Networks with Pressure Driven Demands","year":2018,"lang":"en","type":"article","venue":"Water Resources Management","topic":"Water Systems and Optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Computer science; Snapshot (computer storage); Throttle; Flow control valve; Benchmark (surveying); Programmer; Simulation; Real-time computing; Control engineering; Automotive engineering; Engineering; Embedded system; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001108275,0.0006810338,0.001184991,0.0005973413,0.000625412,0.0006696836,0.001803874,0.001629535,0.006502538],"category_scores_gemma":[0.003163022,0.000668688,0.001018455,0.0005853326,0.0005642881,0.0008536405,0.001054207,0.001491638,0.0004654805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000703675,"about_ca_system_score_gemma":0.001385048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01498966,"about_ca_topic_score_gemma":0.009990223,"domain_scores_codex":[0.9997212,0.0001342082,0.00001272788,0.0000334548,0.00004988393,0.00004840074],"domain_scores_gemma":[0.9982268,0.00130691,0.0001049246,0.00008727088,0.0001797497,0.00009422158],"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":[0.00003389502,0.00002322162,0.0002088625,0.00002567405,0.00002269802,0.00003288456,0.00001466839,0.9933055,0.0002804161,0.002814357,0.0002373159,0.003000614],"study_design_scores_gemma":[0.000006507771,0.000004168725,0.00002053155,0.000001743991,0.000002226849,0.000002732024,0.00000214316,0.9993031,0.00003681313,0.0005011862,0.0001172515,0.000001558483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04374507,0.0003097556,0.9469727,0.0003165302,0.0001393225,0.0001338064,0.0004303647,0.0006208422,0.0073316],"genre_scores_gemma":[0.7392586,0.0003789261,0.2507102,0.0002056693,0.00009481808,0.0007313283,0.0004885755,0.0004353783,0.007696425],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01498966,"threshold_uncertainty_score":0.02980477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005942184055577788,"score_gpt":0.2129468992974643,"score_spread":0.2070047152418865,"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."}}