Application of Large Language Models to Predict Enteric Viruses Removal Using Surrogate Indicators
≈ 0.71-0.89). Although leave-one-location-out validation revealed reduced cross-facility transferability, CALM-VR provides a reproducible, quality-controlled framework for improving enteric virus removal prediction under data-scarce conditions and advancing wastewater surveillance.
Authors
- Diego Rosso (ORCID: https://orcid.org/0000-0002-6879-3110)
- Sunny C. Jiang (ORCID: https://orcid.org/0000-0002-4993-8038)
- Pooria Ghorbani Bam
Institutions
- University of California System (US)
- NexTalk (United States) (US)
Publication Details
- Journal
- Environmental Science & Technology
- Published
- 2026-07-26
- DOI
- https://doi.org/10.1021/acs.est.6c04967
- Primary Topic
- SARS-CoV-2 detection and testing
- Type
- article
- Field-Weighted Citation Impact
- 0.00