The sports nutrition knowledge of large language model (LLM) artificial intelligence (AI) chatbots: An assessment of accuracy, completeness, clarity, quality of evidence, and test-retest reliability.
<h4>Background</h4>Generative artificial intelligence (AI) chatbots are increasingly utilised in various domains, including sports nutrition. Despite their growing popularity, there is limited evidence on the accuracy, completeness, clarity, evidence quality, and test-retest reliability...
Saved in:
| Main Authors: | Thomas P J Solomon, Matthew J Laye |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0325982 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The sports nutrition knowledge of large language model (LLM) artificial intelligence (AI) chatbots: An assessment of accuracy, completeness, clarity, quality of evidence, and test-retest reliability
by: Thomas P. J. Solomon, et al.
Published: (2025-01-01) -
Aurel_AI: Automating an Institutional Help Desk Using an LLM Chatbot
by: Diego Ordóñez-Camacho, et al.
Published: (2024-10-01) -
SeniorSafeAI: LLM-based Chatbot to Assist Senior Citizen Victims of Cybercrime
by: Mai Ly Dinh, et al.
Published: (2025-05-01) -
Development and evaluation of LLM-based suicide intervention chatbot
by: Xueting Cui, et al.
Published: (2025-08-01) -
Test-retest reliability of regression dynamic causal modeling
by: Stefan Frässle, et al.
Published: (2022-02-01)