{"id":"W2050732669","doi":"10.2495/ws130161","title":"Optimal operation of water pumping stations","year":2013,"lang":"en","type":"article","venue":"WIT transactions on ecology and the environment","topic":"Water Systems and Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Electricity; Reliability (semiconductor); Energy consumption; Scheduling (production processes); Differential evolution; Total cost; Water supply; Mathematical optimization; Reliability engineering; Environmental science; Engineering; Environmental engineering; Power (physics); Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006510632,0.0000542128,0.00007380742,0.00002858873,0.00009819125,0.000009205225,0.00002665547,0.00003800846,0.0005376848],"category_scores_gemma":[3.140553e-7,0.00003286645,0.00001817709,0.00001078438,0.00006328479,0.00007530342,0.000001237894,0.00005552974,0.00009434255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001662994,"about_ca_system_score_gemma":0.00000106571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001527481,"about_ca_topic_score_gemma":0.00001591795,"domain_scores_codex":[0.9996798,0.00002794575,0.0001216576,0.00005969784,0.0000337584,0.00007716258],"domain_scores_gemma":[0.9998762,0.00002135348,0.000008916913,0.00007470615,0.000003261,0.0000155759],"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":[0.000004276741,0.00001700147,0.00002886421,0.000006283167,0.00003273833,7.914767e-8,0.0006150426,0.9980584,0.0006240195,0.0001038885,0.00001497532,0.00049443],"study_design_scores_gemma":[0.002062231,0.0001493045,0.008192581,0.00001221296,0.00008452232,0.000009205337,0.0004800418,0.940881,0.04621469,0.0003387121,0.001373656,0.0002018367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4323382,0.00002058858,0.5662774,0.000465524,0.0001225879,0.0003013887,0.00000458299,0.00002331398,0.0004464388],"genre_scores_gemma":[0.9987425,0.00007824576,0.0005833644,0.00002308508,0.000007157322,0.0001212052,0.000005684383,0.000006817723,0.0004319831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5664043,"threshold_uncertainty_score":0.5887272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003386997626334863,"score_gpt":0.1444101308207079,"score_spread":0.141023133194373,"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."}}