{"id":"W3120071516","doi":"10.5194/acp-2020-1195","title":"Estimating 2010–2015 Anthropogenic and Natural Methane Emissions in Canada using ECCC Surface and GOSAT Satellite Observations","year":2021,"lang":"en","type":"article","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; York University","funders":"Japan Aerospace Exploration Agency; Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; University of Leicester; Environment and Climate Change Canada; National Aeronautics and Space Administration","keywords":"Environmental science; Greenhouse gas; Methane; Wetland; Atmospheric sciences; Satellite; Methane emissions; Emission inventory; Boreal; Atmospheric methane; Climatology; Meteorology; Geography; Ecology; Air quality index; Geology","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":[0.0004815769,0.0007394024,0.0002611861,0.0008596547,0.0008980476,0.0006532656,0.0006181255,0.0003572215,0.001136387],"category_scores_gemma":[0.0009209101,0.0003056824,0.0009970042,0.0013142,0.0005116623,0.0004015584,0.0004754979,0.000468032,0.0001860527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01331656,"about_ca_system_score_gemma":0.01487193,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9886134,"about_ca_topic_score_gemma":0.9887478,"domain_scores_codex":[0.999768,0.00001614114,0.00000745185,0.00005273111,0.00009672244,0.00005891176],"domain_scores_gemma":[0.9995958,0.00003693421,0.00003304254,0.00001712274,0.0002768706,0.00004026187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000325435,0.00009470436,0.3905816,0.000148657,0.0006226018,0.0001690314,0.0002465501,0.5674608,0.004588487,0.00206697,0.009231163,0.02446399],"study_design_scores_gemma":[0.00008296179,0.0000332098,0.393286,0.00005135469,0.0001674775,0.00003897607,0.0004021482,0.5914375,0.005129552,0.0007669554,0.008506012,0.00009792988],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9660026,0.0004363544,0.006482636,0.0003141801,0.00002396582,0.00004155564,0.02109809,0.0005271537,0.005073551],"genre_scores_gemma":[0.9719881,0.0002108075,0.007021865,0.00006590071,0.000007528433,0.00001556936,0.01901994,0.00007231858,0.001597993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01331656,"threshold_uncertainty_score":0.09661889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01824771003661803,"score_gpt":0.2401968436164166,"score_spread":0.2219491335797986,"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."}}