Unmasking bias in the evidence ecosystem: a panoramic analysis of 311,751 meta-analyses using an artificial intelligence agent-based approach.

Chen X, She Z, Yang S, Chu M, Zhou Y

DOI: 10.7189/jogh.16.03029
Published: 2026 Sep 4
Container: Journal of global health
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.7189/jogh.16.03029,
  title = {Unmasking bias in the evidence ecosystem: a panoramic analysis of 311,751 meta-analyses using an artificial intelligence agent-based approach.},
  author = {Chen X and She Z and Yang S and Chu M and Zhou Y},
  year = {2026},
  journal = {Journal of global health},
  doi = {10.7189/jogh.16.03029},
  url = {https://doi.org/10.7189/jogh.16.03029}
}

RIS

TY  - JOUR
TI  - Unmasking bias in the evidence ecosystem: a panoramic analysis of 311,751 meta-analyses using an artificial intelligence agent-based approach.
AU  - Chen X
AU  - She Z
AU  - Yang S
AU  - Chu M
AU  - Zhou Y
PY  - 2026
JO  - Journal of global health
DO  - 10.7189/jogh.16.03029
UR  - https://doi.org/10.7189/jogh.16.03029
ER  -

APA

X, C., Z, S., S, Y., M, C., & Y, Z. (2026). Unmasking bias in the evidence ecosystem: a panoramic analysis of 311,751 meta-analyses using an artificial intelligence agent-based approach.. Journal of global health. https://doi.org/10.7189/jogh.16.03029

Source records

pubmed · retrieved 2026-09-25T02:34:00.022Z