Interoperability of machine learning classifiers across LC-MS platforms for non-targeted authentication of honey botanical origin.
- DOI
- 10.1016/j.aca.2026.345986
- Published
- 2026 Nov 1
- Container
- Analytica chimica acta
- Publisher
- Not recorded
- Open access
- unknown
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BibTeX
@article{allodium:10.1016/j.aca.2026.345986,
title = {Interoperability of machine learning classifiers across LC-MS platforms for non-targeted authentication of honey botanical origin.},
author = {Chahal S and Tian L and Balogh F and Hindle R and Hunt K and Baesu A and Feng YL and Karboune S and De Leoz ML and Anumol T and Cuthbertson D and Bayen S},
year = {2026},
journal = {Analytica chimica acta},
doi = {10.1016/j.aca.2026.345986},
url = {https://doi.org/10.1016/j.aca.2026.345986}
}RIS
TY - JOUR TI - Interoperability of machine learning classifiers across LC-MS platforms for non-targeted authentication of honey botanical origin. AU - Chahal S AU - Tian L AU - Balogh F AU - Hindle R AU - Hunt K AU - Baesu A AU - Feng YL AU - Karboune S AU - De Leoz ML AU - Anumol T AU - Cuthbertson D AU - Bayen S PY - 2026 JO - Analytica chimica acta DO - 10.1016/j.aca.2026.345986 UR - https://doi.org/10.1016/j.aca.2026.345986 ER -
APA
S, C., L, T., F, B., R, H., K, H., A, B., YL, F., S, K., ML, D. L., T, A., D, C., & S, B. (2026). Interoperability of machine learning classifiers across LC-MS platforms for non-targeted authentication of honey botanical origin.. Analytica chimica acta. https://doi.org/10.1016/j.aca.2026.345986
Source records
- pubmed · retrieved 2026-09-25T13:08:19.361Z