{"id":"W4409190563","doi":"10.1029/2024gb008310","title":"The North American Greenhouse Gas Budget: Emissions, Removals, and Integration for CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub>O (2010–2019): Results From the Second REgional Carbon Cycle Assessment and Processes Study (RECCAP2)","year":2025,"lang":"en","type":"article","venue":"Global Biogeochemical Cycles","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Natural Resources Canada; Canadian Forest Service","funders":"Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; National Natural Science Foundation of China; California Institute of Technology; Jet Propulsion Laboratory; National Aeronautics and Space Administration","keywords":"Greenhouse gas; Environmental science; Geology; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007731753,0.0006898923,0.0002888068,0.0006258019,0.0003614243,0.000888126,0.0004033472,0.0004412647,0.0006988388],"category_scores_gemma":[0.0004914519,0.0002898307,0.0006126921,0.001923445,0.0002056085,0.0007871651,0.0003658523,0.000436204,0.0002346357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002628339,"about_ca_system_score_gemma":0.003264737,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5075333,"about_ca_topic_score_gemma":0.5959057,"domain_scores_codex":[0.9997962,0.00003355368,0.00001111187,0.0000489069,0.00008216344,0.00002810448],"domain_scores_gemma":[0.9996582,0.00002610157,0.00005623028,0.00002445136,0.0002052296,0.00002978478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009261861,0.0004423918,0.7023984,0.0008365271,0.002047889,0.0004960161,0.0003794653,0.1079524,0.01381408,0.002071291,0.08751932,0.08111595],"study_design_scores_gemma":[0.00008693594,0.00004232227,0.896874,0.00006686328,0.0005101266,0.00005509451,0.0003893034,0.06057687,0.007290664,0.0005947927,0.0334471,0.00006610875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.910939,0.003103036,0.002655324,0.002781939,0.0001451647,0.00008057343,0.0681088,0.0005569804,0.01162911],"genre_scores_gemma":[0.9399701,0.001929515,0.00526571,0.0005517991,0.00005553306,0.0001382941,0.04731272,0.00009015531,0.004686029],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5075333,"threshold_uncertainty_score":0.9907339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007033979078767538,"score_gpt":0.2339123130632461,"score_spread":0.2268783339844786,"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."}}