{"id":"W2045300051","doi":"10.1016/j.jenvman.2007.10.011","title":"An inexact dynamic optimization model for municipal solid waste management in association with greenhouse gas emission control","year":2007,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Water resources management and optimization","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Greenhouse gas; Minification; Municipal solid waste; Implementation; Environmental science; Integer programming; Computer science; Environmental economics; Environmental engineering; Waste management; Engineering; Ecology; Algorithm","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":[0.001186652,0.0009792177,0.002107304,0.0006176576,0.0009053322,0.001991401,0.001240965,0.003795701,0.003145453],"category_scores_gemma":[0.003041644,0.001038328,0.0009091976,0.0007412296,0.001403892,0.001287664,0.00157733,0.001610981,0.0003008776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001332213,"about_ca_system_score_gemma":0.001830292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03031277,"about_ca_topic_score_gemma":0.0138639,"domain_scores_codex":[0.9994911,0.0001838792,0.00002499402,0.0001015533,0.0001149782,0.00008345764],"domain_scores_gemma":[0.9988655,0.0006988319,0.0001410178,0.00004489008,0.0001769819,0.00007291105],"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":[0.00001166533,0.000005965845,0.00005533321,0.000006032623,0.000004249799,0.00001544138,0.000005329512,0.9984155,0.00007010293,0.000866611,0.00004983683,0.0004939534],"study_design_scores_gemma":[0.000003179273,0.000005224158,0.00002242818,7.464653e-7,0.000001949528,0.000001420856,0.000002128801,0.9996485,0.00003183328,0.0002263566,0.00005478394,0.000001558344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1671005,0.0005634744,0.8090505,0.001571896,0.0002483486,0.000110729,0.0004624111,0.0004332695,0.02045889],"genre_scores_gemma":[0.9716204,0.0001711965,0.01938617,0.0001058248,0.00003384284,0.0001281658,0.0001669795,0.00005686576,0.008330602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03031277,"threshold_uncertainty_score":0.06027269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004135208624583174,"score_gpt":0.1976681364627651,"score_spread":0.1935329278381819,"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."}}