{"id":"W1547346277","doi":"10.1111/geb.12307","title":"Estimating global natural wetland methane emissions using process modelling: spatio‐temporal patterns and contributions to atmospheric methane fluctuations","year":2015,"lang":"en","type":"article","venue":"Global Ecology and Biogeography","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Program for New Century Excellent Talents in University; Northwest A and F University; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Wetland; Environmental science; Atmospheric methane; Methane; Temperate climate; Methanogenesis; Greenhouse gas; Atmospheric sciences; Methane emissions; Climatology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002235735,0.0002499867,0.0002668659,0.000006239631,0.000285266,0.00003473913,0.0001475616,0.0001695354,0.00006014165],"category_scores_gemma":[0.00005851354,0.0002230097,0.00006135561,0.0006187448,0.0003664693,0.0002026802,0.0002583314,0.0001255962,0.00001021791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002381575,"about_ca_system_score_gemma":0.00003889579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002559444,"about_ca_topic_score_gemma":0.0009189037,"domain_scores_codex":[0.9985111,0.00007653555,0.0002713002,0.000475771,0.0002157188,0.0004495693],"domain_scores_gemma":[0.9992006,0.00002790912,0.0001139186,0.0001471969,0.00002527147,0.0004850856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000416878,0.00006129999,0.8253508,0.000005054935,0.00003525793,0.000006950523,0.00008092704,0.1729261,0.00002645403,0.00006321233,0.00003693959,0.001365313],"study_design_scores_gemma":[0.0008439207,0.0002105432,0.4228678,0.00001603096,0.0001394662,0.0001269052,0.0004082453,0.568786,0.00001234835,0.005921781,0.0002812954,0.0003856778],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8904721,0.000171634,0.1079974,0.0004262465,0.0002206102,0.0003104634,0.0001919555,0.00005424792,0.0001553953],"genre_scores_gemma":[0.8911794,0.00001724269,0.1083275,0.0003397072,0.00003384152,0.00001920669,0.00006560132,0.000006865063,0.00001068258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4024831,"threshold_uncertainty_score":0.9094073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01075183051578895,"score_gpt":0.2645454797727055,"score_spread":0.2537936492569166,"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."}}