A unified machine-learning framework for ab initio multiscale modeling of liquids.
- DOI
- 10.1073/pnas.2610049123
- Published
- 2026 Jul 28
- Container
- Proceedings of the National Academy of Sciences of the United States of America
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- supportingOpen access status: Normalized open-access status: open.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1073/pnas.2610049123,
title = {A unified machine-learning framework for ab initio multiscale modeling of liquids.},
author = {Bui AT and Cox SJ},
year = {2026},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
doi = {10.1073/pnas.2610049123},
url = {https://doi.org/10.1073/pnas.2610049123}
}RIS
TY - JOUR TI - A unified machine-learning framework for ab initio multiscale modeling of liquids. AU - Bui AT AU - Cox SJ PY - 2026 JO - Proceedings of the National Academy of Sciences of the United States of America DO - 10.1073/pnas.2610049123 UR - https://doi.org/10.1073/pnas.2610049123 ER -
APA
AT, B., & SJ, C. (2026). A unified machine-learning framework for ab initio multiscale modeling of liquids.. Proceedings of the National Academy of Sciences of the United States of America. https://doi.org/10.1073/pnas.2610049123
Source records
- pubmed · retrieved 2026-11-10T10:33:41.750Z