{"id":"W4402276545","doi":"10.1038/s41561-024-01524-z","title":"Global riverine land-to-ocean carbon export constrained by observations and multi-model assessment","year":2024,"lang":"en","type":"article","venue":"Nature Geoscience","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Fundamental Research Funds for the Central Universities; Horizon 2020 Framework Programme; Agence Nationale de la Recherche; Natural Science Foundation of Beijing Municipality; China Postdoctoral Science Foundation; National Natural Science Foundation of China; National Science Foundation","keywords":"Environmental science; Carbon cycle; Climatology; Carbon flux; Carbon fibers; Geology; Oceanography; Computer science; Ecosystem","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":[0.001342008,0.0008029906,0.0008693393,0.0005584711,0.0005381198,0.001182096,0.001118721,0.001506857,0.001329868],"category_scores_gemma":[0.00227282,0.000748469,0.001416261,0.0008647792,0.0007170619,0.001596706,0.0005812822,0.0008191906,0.0002400651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001405117,"about_ca_system_score_gemma":0.001743267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08319056,"about_ca_topic_score_gemma":0.05811793,"domain_scores_codex":[0.9997386,0.00008364128,0.00001829473,0.00009797718,0.00002156896,0.00003977246],"domain_scores_gemma":[0.9988747,0.0005724504,0.0001169265,0.000194117,0.0001522594,0.00008945062],"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":[0.0001253951,0.00005111311,0.01140629,0.00002569798,0.0001467291,0.00004885338,0.00001375295,0.9853496,0.0007530447,0.0003557723,0.0003378095,0.001385923],"study_design_scores_gemma":[0.00009147357,0.00003450154,0.0130419,0.000007937738,0.00006009296,0.00001197593,0.00001919652,0.9852902,0.0005684096,0.0005942999,0.0002488497,0.00003111985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902074,0.00009234024,0.003742249,0.0002438937,0.00002258904,0.00001885365,0.003770505,0.0002354427,0.001666747],"genre_scores_gemma":[0.995846,0.00003663407,0.001855386,0.00002830095,0.00000723903,0.00002204812,0.001794438,0.00003710254,0.0003728733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08319056,"threshold_uncertainty_score":0.1654127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213741965294886,"score_gpt":0.2506383246741103,"score_spread":0.2385009050211614,"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."}}