{"id":"W3137169862","doi":"10.1002/aic.17256","title":"Sustainable optimization of waste management network over extended planning time horizon","year":2021,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Time horizon; Maximization; Multi-objective optimization; Sustainability; Mathematical optimization; Minification; Pareto principle; Profit maximization; Municipal solid waste; Linear programming; Profit (economics); Net present value; Integer programming; Range (aeronautics); Pareto optimal; Work (physics); Computer science; Operations research; Environmental economics; Engineering; Waste management; Economics; Mathematics; Production (economics); Microeconomics","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":[0.001329006,0.0008950352,0.001030376,0.0007753689,0.00058759,0.001647134,0.0008952591,0.001206767,0.003886564],"category_scores_gemma":[0.001797312,0.0007876277,0.0007073032,0.0009811159,0.0006403817,0.001142304,0.0006370574,0.0009800559,0.0002326138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002408576,"about_ca_system_score_gemma":0.002051493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01475899,"about_ca_topic_score_gemma":0.01211159,"domain_scores_codex":[0.9994999,0.0002243973,0.00001256518,0.00007183367,0.00006849496,0.0001227868],"domain_scores_gemma":[0.999401,0.0003250081,0.0001116732,0.00001843368,0.00007762171,0.00006625863],"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":[0.00001358807,0.000008242407,0.0001065845,0.000008465459,0.000007400144,0.00001715571,0.000003828574,0.9980903,0.00007938761,0.0008680518,0.00006729872,0.0007297004],"study_design_scores_gemma":[0.000004093636,0.0000182572,0.00008802168,0.000003955621,0.000005611325,0.000003712101,0.000009961059,0.9989358,0.00006391108,0.0007130133,0.0001516299,0.000002069209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4157266,0.001829282,0.5465893,0.001540395,0.0001357282,0.000273844,0.001121415,0.0003131665,0.03247019],"genre_scores_gemma":[0.9576709,0.0004195322,0.03195475,0.00007844201,0.00002111627,0.000242127,0.0002829586,0.00004725764,0.00928293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01475899,"threshold_uncertainty_score":0.02934617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007100528898212884,"score_gpt":0.2295294868521976,"score_spread":0.2224289579539847,"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."}}