Note: This study found no significant biological effects under its experimental conditions. We include all studies for scientific completeness.
Xiang Y, Xu L, Sun Y, Hu C, Lv L
No Effects Found
Authors not listed · 2025
This AI translation study was incorrectly categorized as EMF health research and contains no electromagnetic field data.
Plain English Summary
Summary written for general audiences
This study appears to be misclassified in the EMF Research Hub database. The research actually focuses on artificial intelligence and machine translation capabilities of large language models, not electromagnetic field health effects. The paper describes developing improved multilingual translation software, with no connection to EMF exposure or biological systems.
Cite This Study
Unknown (2025). Xiang Y, Xu L, Sun Y, Hu C, Lv L.
Show BibTeX
@article{xiang_y_xu_l_sun_y_hu_c_lv_l_ce3909,
author = {Unknown},
title = {Xiang Y, Xu L, Sun Y, Hu C, Lv L},
year = {2025},
doi = {10.48550/arXiv.2502.02481},
}Quick Questions About This Study
This appears to be a database categorization error. The study focuses on machine translation software development and contains no electromagnetic field research or health data whatsoever.
The study doesn't address EMF exposure from AI systems. It only evaluates translation performance across 28 languages without examining electromagnetic emissions or biological effects.
This study doesn't investigate EMF emissions. While AI systems do generate electromagnetic fields during operation, this research only measures translation accuracy, not radiation exposure.
The study provides no EMF frequency data. It focuses entirely on software performance metrics and translation capabilities across different languages, not electromagnetic emissions.
PFMS is a software training method unrelated to EMF exposure. The study examines how different data combinations improve translation quality, not electromagnetic field effects.