{"id":"W4416077496","doi":"10.1021/acsestair.5c00127","title":"Comparison of Landfill Methane Emission Quantification Using Multiple Observation Methods","year":2025,"lang":"en","type":"article","venue":"ACS ES&T Air","topic":"Landfill Environmental Impact Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Environment and Climate Change Canada","funders":"Office of Energy Research and Development; Natural Sciences and Engineering Research Council of Canada; Natural Resources Canada; Canadian Space Agency; European Space Agency; Environment and Climate Change Canada; Canada Foundation for Innovation; Ontario Research Foundation","keywords":"Methane; Methane emissions; Range (aeronautics); Greenhouse gas; Landfill gas; Environmental monitoring; Software deployment","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003985201,0.0001358163,0.0002565985,0.00004483307,0.0001251959,0.000007293702,0.000174145,0.00007951119,0.0001068486],"category_scores_gemma":[0.0002499137,0.0001131725,0.00005003657,0.0003257339,0.0001329949,0.000205978,0.0002425064,0.00009004918,0.00002442112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001888202,"about_ca_system_score_gemma":0.00000689996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008863905,"about_ca_topic_score_gemma":0.00003173192,"domain_scores_codex":[0.9988676,0.0001415241,0.0003431457,0.0002538557,0.0002139956,0.0001799271],"domain_scores_gemma":[0.9992496,0.0002101345,0.000189597,0.0002986356,0.000008073141,0.00004401038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001823867,0.00008354947,0.4881915,0.00001289242,0.00001473214,1.315555e-7,0.00030732,0.002499217,0.4991054,0.00001157511,0.0003661577,0.009389326],"study_design_scores_gemma":[0.0002622269,0.00002566013,0.3718638,0.00002631968,0.00003614869,3.851581e-7,0.0001347129,0.01837869,0.6068811,0.0001405955,0.002153612,0.00009677008],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670604,0.0001827892,0.03043031,0.0002353256,0.000153508,0.0002327935,0.000007846655,0.00003649907,0.001660473],"genre_scores_gemma":[0.9619527,0.00002177713,0.03737735,0.0001129941,0.000009842824,0.000008959149,0.00002845101,0.000009814609,0.0004781388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1163277,"threshold_uncertainty_score":0.4615041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1063894381527298,"score_gpt":0.4154742713176754,"score_spread":0.3090848331649456,"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."}}