The Physical Fidelity Gap as an Evidence-Traceability Problem in AI Uncertainty Quantification: A Structured Review
- DOI
- 10.3390/s26175447
- Published
- 2026-08-28
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- 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.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- 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.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.3390/s26175447,
title = {The Physical Fidelity Gap as an Evidence-Traceability Problem in AI Uncertainty Quantification: A Structured Review},
author = {Lin Guo and Aiwen Ma and Heng Zhou and Zilong Liu and Xingchuang Xiong},
year = {2026},
journal = {Sensors},
doi = {10.3390/s26175447},
url = {https://doi.org/10.3390/s26175447}
}RIS
TY - JOUR TI - The Physical Fidelity Gap as an Evidence-Traceability Problem in AI Uncertainty Quantification: A Structured Review AU - Lin Guo AU - Aiwen Ma AU - Heng Zhou AU - Zilong Liu AU - Xingchuang Xiong PY - 2026 JO - Sensors DO - 10.3390/s26175447 UR - https://doi.org/10.3390/s26175447 ER -
APA
Guo, L., Ma, A., Zhou, H., Liu, Z., & Xiong, X. (2026). The Physical Fidelity Gap as an Evidence-Traceability Problem in AI Uncertainty Quantification: A Structured Review. Sensors. https://doi.org/10.3390/s26175447
Source records
- crossref · retrieved 2026-09-25T14:30:11.354Z