Evidence map›Paper›PMID 39687205›Full record

ArticleNational science review2024

Low latency carbon budget analysis reveals a large decline of the land carbon sink in 2023.

Piyu Ke, Philippe Ciais, Stephen Sitch, Wei Li, Ana Bastos, Zhu Liu, Yidi Xu, Xiaofan Gui, Jiang Bian, Daniel S Goll and 6 more

Abstract read
In one paragraph

Article in National science review, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Global daily COScientific data · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Net Ecosystem COGlobal change biology · 2025
    Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Piyu KeDepartment of Earth System Science, Tsinghua University, Beijing 100084, China.ORCID https://orcid.org/0000-0003-0353-6313
Philippe CiaisLaboratoire des Sciences du Climat et de l'Environnement, University Paris Saclay CEA CNRS, Gif sur Yvette 91191, France.
Stephen SitchFaculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QF, United Kingdom.
Wei LiDepartment of Earth System Science, Tsinghua University, Beijing 100084, China.
Ana BastosInstitute for Earth System Science and Remote Sensing, Leipzig University, Leipzig 04103, Germany.
Zhu LiuDepartment of Earth System Science, Tsinghua University, Beijing 100084, China.ORCID https://orcid.org/0000-0002-8968-7050
Yidi XuLaboratoire des Sciences du Climat et de l'Environnement, University Paris Saclay CEA CNRS, Gif sur Yvette 91191, France.
Xiaofan GuiMachine learning group, Microsoft research, Beijing 100080, China.ORCID https://orcid.org/0000-0001-8259-5471
Jiang BianMachine learning group, Microsoft research, Beijing 100080, China.
Daniel S GollLaboratoire des Sciences du Climat et de l'Environnement, University Paris Saclay CEA CNRS, Gif sur Yvette 91191, France.
Yi XiLaboratoire des Sciences du Climat et de l'Environnement, University Paris Saclay CEA CNRS, Gif sur Yvette 91191, France.
Wanjing LiDepartment of Earth System Science, Tsinghua University, Beijing 100084, China.
Michael O'SullivanFaculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QF, United Kingdom.
Jefferson Goncalves De SouzaFaculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QF, United Kingdom.
Pierre FriedlingsteinFaculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QF, United Kingdom.
Frédéric ChevallierLaboratoire des Sciences du Climat et de l'Environnement, University Paris Saclay CEA CNRS, Gif sur Yvette 91191, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In 2023, the CO

Indexed as

artificial intelligence emulators of modelsEl Niño 2023Global Carbon Budget

Identifiers

PMID39687205
PMCPMC11648560

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.