A collaborative network of digital twins for anomaly detection applications of complex systems. Snitch Digital Twin concept
- DOI
- 10.1016/j.compind.2022.103767
- Published
- 2023-01
- Container
- Computers in Industry
- Publisher
- Elsevier BV
- 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:10.1016/j.compind.2022.103767,
title = {A collaborative network of digital twins for anomaly detection applications of complex systems. Snitch Digital Twin concept},
author = {Pablo Calvo-Bascones and Alexandre Voisin and Phuc Do and Miguel A. Sanz-Bobi},
year = {2023},
journal = {Computers in Industry},
doi = {10.1016/j.compind.2022.103767},
url = {https://doi.org/10.1016/j.compind.2022.103767}
}RIS
TY - JOUR TI - A collaborative network of digital twins for anomaly detection applications of complex systems. Snitch Digital Twin concept AU - Pablo Calvo-Bascones AU - Alexandre Voisin AU - Phuc Do AU - Miguel A. Sanz-Bobi PY - 2023 JO - Computers in Industry DO - 10.1016/j.compind.2022.103767 UR - https://doi.org/10.1016/j.compind.2022.103767 ER -
APA
Calvo-Bascones, P., Voisin, A., Do, P., & Sanz-Bobi, M. A. (2023). A collaborative network of digital twins for anomaly detection applications of complex systems. Snitch Digital Twin concept. Computers in Industry. https://doi.org/10.1016/j.compind.2022.103767
Source records
- crossref · retrieved 2026-09-25T22:01:25.317Z