{"id":"W1796291915","doi":"","title":"A dynamic modelling approach to evaluate GHG emissions from wastewater treatment plants","year":2012,"lang":"en","type":"article","venue":"Lund University Publications (Lund University)","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Vlaamse regering; Ministero dello Sviluppo Economico; Fonds Wetenschappelijk Onderzoek; Ministère du Développement Économique, de l’Innovation et de l’Exportation","keywords":"Greenhouse gas; Environmental science; Sewage treatment; Wastewater; Waste management; Environmental engineering; Engineering; Geology; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005965337,0.001159322,0.0006740206,0.0007932275,0.0004563686,0.001214883,0.0009684723,0.001312561,0.001415682],"category_scores_gemma":[0.001108405,0.0004119801,0.001171893,0.001124681,0.0003835434,0.0007565666,0.0006948367,0.0007595388,0.0002028432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001695907,"about_ca_system_score_gemma":0.001136918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01953627,"about_ca_topic_score_gemma":0.008193895,"domain_scores_codex":[0.9996045,0.0001430469,0.00002360307,0.00007097117,0.0001112874,0.00004661599],"domain_scores_gemma":[0.9996873,0.0001632558,0.00003512644,0.00002725741,0.00007358574,0.00001346044],"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":[0.00001477744,0.00001464152,0.000304146,0.00001885389,0.00001491871,0.00001149572,0.000006232932,0.9953899,0.0009707459,0.001162349,0.00007544104,0.002016378],"study_design_scores_gemma":[0.000008038949,0.00005152836,0.0004362837,0.000004758789,0.00001049543,0.000006829403,0.00001294596,0.9966227,0.0008097625,0.001300784,0.0007263116,0.000009609689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3126653,0.0009393986,0.6298059,0.0006317304,0.0001253254,0.0004716741,0.0039099,0.001064906,0.05038593],"genre_scores_gemma":[0.965028,0.0004689199,0.02922402,0.00007517121,0.00001981524,0.0005413599,0.0009998173,0.00006095991,0.003581978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01953627,"threshold_uncertainty_score":0.03884506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02880926159263742,"score_gpt":0.2093520145886847,"score_spread":0.1805427529960473,"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."}}