{"id":"W4403189365","doi":"10.1038/s43247-024-01728-6","title":"Hybrid bottom-up and top-down framework resolves discrepancies in Canada’s oil and gas methane inventories","year":2024,"lang":"en","type":"article","venue":"Communications Earth & Environment","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Oceanic and Atmospheric Administration; University of Lethbridge; Environment and Climate Change Canada; National Aeronautics and Space Administration","keywords":"Top-down and bottom-up design; Methane; Methane emissions; Environmental science; Fossil fuel; Petroleum engineering; Greenhouse gas; Geology; Oceanography; Computer science; Engineering; Chemistry; Waste management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001074848,0.0009168076,0.0005038552,0.0007778484,0.0007472727,0.001119456,0.001291275,0.0003872976,0.0009102247],"category_scores_gemma":[0.001595869,0.0003042998,0.0005383285,0.0005852378,0.0004926322,0.0006946539,0.001059117,0.0007436937,0.0002150574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001966663,"about_ca_system_score_gemma":0.006313341,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5893212,"about_ca_topic_score_gemma":0.6269973,"domain_scores_codex":[0.9995397,0.00007296167,0.00001801868,0.00009339969,0.0001726969,0.0001033064],"domain_scores_gemma":[0.999393,0.00008790322,0.00004466923,0.00006274543,0.0003723752,0.000039225],"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":[0.0001850389,0.0001262833,0.02678871,0.0001202337,0.0003433529,0.0001520356,0.0001834977,0.7461391,0.01375367,0.004387067,0.005005718,0.2028153],"study_design_scores_gemma":[0.000008305886,0.00001088595,0.002675385,0.000006439892,0.00002871926,0.000006817266,0.00003862281,0.9939069,0.001844021,0.000662144,0.0007967456,0.00001506278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3420248,0.0008043032,0.6410603,0.0008859231,0.0001445142,0.0001551781,0.001761014,0.004559976,0.008603925],"genre_scores_gemma":[0.8308783,0.0001546019,0.1655895,0.0001316243,0.00004864129,0.00003835445,0.001287731,0.0001711491,0.001700215],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4106788,"threshold_uncertainty_score":0.8261948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01013546609506246,"score_gpt":0.2139531801484329,"score_spread":0.2038177140533704,"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."}}