The DOI matches its Crossref record.
PubMed Central: The GenBank of the published literature
Open accessAbstract
Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans the biological, physical, and social sciences.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
A Multimodal Biomedical Foundation Model Trained from Fifteen Million Image–Text Pairs
Zhang, S., Xu, Y., Usuyama, N., Xu, H., Bagga, J., Tinn, R., Preston, S., Rao, R., Wei, M., Valluri, N., et al. (2025) · NEJM AI · doi:10.1056/aioa2400640 · Cited by 283
ChestXRayBERT: A Pretrained Language Model for Chest Radiology Report Summarization
Cai, X., Liu, S., Han, J., Yang, L., Liu, Z., & Liu, T. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3132724 · Cited by 72
PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
Zhang, X., Wu, C., Zhao, Z., Lin, W., Zhang, Y., Wang, Y., & Xie, W. (2023) · arXiv · doi:10.48550/arxiv.2305.10415 · Cited by 66
“6 million image-text pairs collected from PubMedCentral (PMC)’s OpenAccess subset [31], which covers 2.”
MethodQuilt-1M: One Million Image-Text Pairs for Histopathology
Ikezogwo, W. O., Seyfioglu, M. S., Ghezloo, F., Geva, D. S. C., Mohammed, F. S., Anand, P. K., Krishna, R., & Shapiro, L. (2023) · arXiv · doi:10.48550/arxiv.2306.11207 · Cited by 55
Pelka, O., Friedrich, C. M., Nensa, F., Mönninghoff, C., Bloch, L., Jöckel, K.-H., Schramm, S., Sanchez Hoffmann, S., Winkler, A., Weimar, C., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0236868 · Cited by 22
“[28] to fuse decision values from a multiclass linear kernel Support Vector Machine (SVM) [29] and Random Forest [30] classifiers to predict the modality of subfigures extracted from the PubMed Central (PMC) Open Access Subset [31].”
Method
Metadata
- Authors
- Roberts, R. J.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2001-01-09
- Volume
- 98
- Issue
- 2
- Pages
- 381-382
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2029017735
- Cited by
- 235
- References
- 0
- FWCI
- 13.08
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: PubMed Central: The GenBank of the published literature. https://app.cochat.ai/papers/10.1073/pnas.98.2.381
- The paper
- Roberts, R. J. (2001). PubMed Central: The GenBank of the published literature. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.98.2.381
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
