{"id":"W3212009912","doi":"10.5194/acp-2021-911","title":"Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observations","year":2021,"lang":"en","type":"article","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Defense Science and Engineering Graduate; National Natural Science Foundation of China; National Institute of Advanced Industrial Science and Technology; National Aeronautics and Space Administration","keywords":"Environmental science; Greenhouse gas; Methane; Fossil fuel; Emission inventory; Coal; Climate change; Methane emissions; Environmental protection; Natural resource economics; Climatology; Meteorology; Geography; Air quality index; Economics; Waste management; Geology; Chemistry; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002576137,0.001221544,0.0005820304,0.002123033,0.000361251,0.0007452406,0.001236532,0.0004916794,0.001154802],"category_scores_gemma":[0.003485231,0.0004460425,0.0009936917,0.003325888,0.000262499,0.001945528,0.0009625183,0.000601616,0.0004695347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001389034,"about_ca_system_score_gemma":0.002002734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1580258,"about_ca_topic_score_gemma":0.09251887,"domain_scores_codex":[0.9993462,0.0001380576,0.00006053154,0.0001164099,0.0002454538,0.00009340121],"domain_scores_gemma":[0.9982288,0.0002324602,0.0002383173,0.0003358212,0.0008522036,0.0001123935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001239956,0.0003423231,0.4802204,0.0003619237,0.001114699,0.0004109088,0.0002474884,0.3838439,0.007161638,0.002274906,0.02202611,0.1007557],"study_design_scores_gemma":[0.0003603721,0.0003284842,0.4197375,0.0002642787,0.0005000168,0.0002181086,0.0004772111,0.5138044,0.02254721,0.001854123,0.03963536,0.0002728702],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8245637,0.0005758471,0.02629451,0.0004398394,0.0001595934,0.0002580303,0.1353844,0.002451408,0.009872744],"genre_scores_gemma":[0.7906095,0.0003387084,0.05415397,0.0001362454,0.00004485559,0.0002485888,0.1527862,0.0004712217,0.001210723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1580258,"threshold_uncertainty_score":0.3142118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0283560727942824,"score_gpt":0.2472753570852486,"score_spread":0.2189192842909662,"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."}}