{"id":"W4235495434","doi":"10.32920/ryerson.14652789","title":"Modeling of Methane Gas Generation and Emissions from Landfills","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Landfill Environmental Impact Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Department for Environment, Food and Rural Affairs, UK Government; U.S. Environmental Protection Agency","keywords":"Methane; Landfill gas; Methane gas; Municipal solid waste; Cellulose; Environmental science; Methane emissions; Natural gas; Greenhouse gas; Moisture; Environmental engineering; Waste management; Chemistry; Engineering; Geology; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000335563,0.0007083659,0.0006271462,0.0004889894,0.0004543384,0.0009354562,0.0008732021,0.001180784,0.001311832],"category_scores_gemma":[0.000438879,0.0003573351,0.0008137717,0.0007693318,0.000293048,0.0009031129,0.000462451,0.0005016486,0.0002800609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001437871,"about_ca_system_score_gemma":0.001484276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03168586,"about_ca_topic_score_gemma":0.01582748,"domain_scores_codex":[0.9998277,0.00004586314,0.000009392927,0.00003380159,0.00003964648,0.00004348621],"domain_scores_gemma":[0.9998894,0.00005281654,0.00001609419,0.000007491134,0.00002528598,0.000008941975],"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":[0.00002412606,0.00001572834,0.001378546,0.00002927934,0.00001140573,0.00005776365,0.00001504467,0.9943367,0.0008993784,0.001412355,0.0001030161,0.001716756],"study_design_scores_gemma":[0.000007216467,0.00002223216,0.0005913898,0.000005113597,0.000008604579,0.00001490813,0.00002381099,0.9968119,0.001013538,0.000829887,0.0006643995,0.000007013309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7759945,0.001362511,0.1878025,0.0005520693,0.00009001425,0.0001979051,0.003952958,0.001087607,0.02896005],"genre_scores_gemma":[0.9855878,0.0004120388,0.007726675,0.00001992224,0.0000115416,0.0001231354,0.0007523914,0.00004660731,0.005319918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03168586,"threshold_uncertainty_score":0.06300282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03686273079887859,"score_gpt":0.2582384214733632,"score_spread":0.2213756906744846,"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."}}