{"id":"W4405152432","doi":"10.1016/j.desal.2024.118416","title":"Enhancing the efficiency of electrodialysis brine concentrator to reduce the levelized cost of salt production through dynamic model-based simulations","year":2024,"lang":"en","type":"article","venue":"Desalination","topic":"Membrane-based Ion Separation Techniques","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Current Water Technologies (Canada)","funders":"Bureau of Reclamation; U.S. Department of Energy; Office of Energy Efficiency and Renewable Energy; National Institute of Food and Agriculture; Michigan Department of Agriculture and Rural Development; U.S. Department of Agriculture","keywords":"Brine; Cost of electricity by source; Electrodialysis; Concentrator; Process engineering; Environmental science; Environmental engineering; Forward osmosis; Desalination; Salt water; Waste management; Pulp and paper industry; Engineering; Electricity generation; Chemistry; Reverse osmosis; Membrane; Power (physics); Thermodynamics; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004447257,0.0001129806,0.0001468078,0.0001318745,0.0000775497,0.00003117084,0.0001408234,0.00005145602,0.00002450002],"category_scores_gemma":[0.0002183086,0.00008265362,0.00006373065,0.0008979464,0.00004762899,0.0001534385,0.00000833282,0.0001163127,0.000003577094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001517364,"about_ca_system_score_gemma":0.0001083905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001814742,"about_ca_topic_score_gemma":0.00004864976,"domain_scores_codex":[0.9989235,0.00006272319,0.0004367002,0.0001749887,0.0002720453,0.0001300666],"domain_scores_gemma":[0.9991808,0.0001940638,0.00007482139,0.0002920519,0.0002390606,0.00001920602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008101695,0.00001083467,9.812107e-7,0.00006131919,0.00001086118,4.76108e-8,0.0004217711,0.4932235,0.5040374,0.001145393,0.00006227399,0.001017607],"study_design_scores_gemma":[0.00005356462,0.0000117543,0.000009890963,0.00003909002,0.00002413164,2.907774e-7,0.00001305206,0.4954866,0.5039406,0.0001847081,0.0001929995,0.00004321481],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.351979,0.0001856252,0.6462507,0.0006394997,0.000131728,0.0004939904,0.00002192716,0.0002123647,0.0000851519],"genre_scores_gemma":[0.9967258,0.00002836197,0.002954422,0.00003770049,0.00004091745,0.00008610269,0.00005600143,0.00002502874,0.00004567604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6447468,"threshold_uncertainty_score":0.3370517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01736460645030264,"score_gpt":0.3067832012323936,"score_spread":0.289418594782091,"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."}}