{"id":"W4384698297","doi":"10.1029/2023gl103037","title":"Cold‐Season Methane Fluxes Simulated by GCP‐CH<sub>4</sub> Models","year":2023,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal; Environment and Climate Change Canada","funders":"Bundesministerium für Bildung und Forschung; University of Birmingham; Environmental Restoration and Conservation Agency; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Ministry of Education, Culture, Sports, Science and Technology; Ministry of the Environment, Government of Japan; National Science Foundation","keywords":"Environmental science; Methane; Atmospheric sciences; Snow; Greenhouse gas; Climatology; Climate model; Flux (metallurgy); Winter season; Wetland; Climate change; Meteorology; Geology; Chemistry; Ecology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0004359449,0.0007570137,0.0004526931,0.000301597,0.0004302522,0.0006633644,0.0008798426,0.0007784609,0.001168327],"category_scores_gemma":[0.0008341005,0.0004302176,0.0006775509,0.0004572277,0.0004293969,0.0006808058,0.0003425681,0.0006341049,0.0001919101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001067921,"about_ca_system_score_gemma":0.0008046911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07656671,"about_ca_topic_score_gemma":0.04656354,"domain_scores_codex":[0.9998547,0.00004422949,0.000007333801,0.00004160254,0.00001361648,0.00003843392],"domain_scores_gemma":[0.9996008,0.0001579339,0.0000476051,0.00006784645,0.00006036783,0.0000654124],"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":[0.0003447904,0.00009019279,0.04377443,0.00002241689,0.0001356293,0.00006012044,0.00004288231,0.9484578,0.004004647,0.0003830398,0.0006742134,0.002009839],"study_design_scores_gemma":[0.00009341097,0.00005511142,0.01601021,0.000004529485,0.00003862529,0.00001036883,0.00003836011,0.9806516,0.002426813,0.0002680362,0.0003851981,0.00001775611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965883,0.00002722583,0.001001023,0.00006746675,0.00001094347,0.000008001441,0.0009186715,0.0001724204,0.001205873],"genre_scores_gemma":[0.9980338,0.00001993786,0.0007595504,0.00001894686,0.000004697742,0.0000131716,0.0009038501,0.00003104877,0.0002150125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07656671,"threshold_uncertainty_score":0.1522421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02229771054761497,"score_gpt":0.2712250466400675,"score_spread":0.2489273360924525,"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."}}