{"id":"W4399767347","doi":"10.1021/acs.estlett.4c00280","title":"Toward Enhancing Wastewater Treatment with Resource Recovery in Integrated Assessment and Computable General Equilibrium Models","year":2024,"lang":"en","type":"review","venue":"Environmental Science & Technology Letters","topic":"Water resources management and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"H2020 European Research Council; Division of Chemical, Bioengineering, Environmental, and Transport Systems; McCormick School of Engineering, Northwestern University; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Computable general equilibrium; Resource recovery; Wastewater; Resource (disambiguation); Sewage treatment; Environmental science; Computer science; Process engineering; Economics; Biochemical engineering; Environmental economics; Microeconomics; Environmental engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003034361,0.00129562,0.001691273,0.001366687,0.000225677,0.001632128,0.00184546,0.00186194,0.001808223],"category_scores_gemma":[0.003491129,0.0007003346,0.001879685,0.002667397,0.0006714656,0.00259371,0.001112496,0.002186025,0.00100018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001897953,"about_ca_system_score_gemma":0.002095719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006275749,"about_ca_topic_score_gemma":0.006572644,"domain_scores_codex":[0.9991026,0.0004940893,0.00006388416,0.00008560278,0.0002139181,0.00003999717],"domain_scores_gemma":[0.9988737,0.0007058754,0.00007474848,0.00006387829,0.0002578283,0.00002396286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004225736,0.0001718943,0.0006367286,0.01075169,0.0005342084,0.0001636781,0.0001032087,0.3074278,0.001606424,0.2497231,0.01944184,0.4093972],"study_design_scores_gemma":[0.00005283172,0.0002066474,0.0008434771,0.004539237,0.0004015121,0.0001841444,0.0001287152,0.3772846,0.002806,0.2041036,0.4093128,0.000136452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003175024,0.7483079,0.226228,0.004642778,0.0005415365,0.00008993482,0.0001670421,0.0002462888,0.01660144],"genre_scores_gemma":[0.05535495,0.834297,0.1038235,0.0008632395,0.0005743071,0.0002808913,0.000342342,0.00009974185,0.004364095],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006275749,"threshold_uncertainty_score":0.01604748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01449398304973691,"score_gpt":0.223788034862873,"score_spread":0.2092940518131361,"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."}}