Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

4.0K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The effect of form on equine salt intake.

Journal of equine veterinary science·2026
Same author

Effect of feeder style on intake rate of equine concentrates.

Journal of equine veterinary science·2026
Same author

Unveiling the equine placental transcriptome: A novel study on ICSI-derived pregnancies.

Theriogenology·2025
Same author

Cultivating Inclusivity and Bridging Gaps Through Reverse Mentoring: A Feasibility Study Within the Royal College of Radiologists.

Clinical oncology (Royal College of Radiologists (Great Britain))·2024
Same author

Biomechanical and ergonomic risks associated with cervical musculoskeletal dysfunction amongst surgeons: A systematic review.

The surgeon : journal of the Royal Colleges of Surgeons of Edinburgh and Ireland·2024
Same author

Unveiling Disparities: Exploring Differential Attainment in Postgraduate Training Within Clinical Oncology.

Clinical oncology (Royal College of Radiologists (Great Britain))·2024

Related Experiment Video

Updated: May 4, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

1.3K

Accuracy of large language model-based artificial intelligence tools for equine topics.

S Aldworth-Yang1, S J Coleman1, K O'Reilly1

  • 1Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, 350 W Pitkin Street, Fort Collins, Colorado 80521, USA.

Journal of Equine Veterinary Science
|May 2, 2026
PubMed
Summary

Artificial intelligence (AI) platforms show potential for equine information but struggle with complex topics. While capable of answering basic questions, their accuracy and thoroughness vary, falling short of expert knowledge.

Keywords:
ChatGPTExtension factsheetsExtensionBotMicrosoft copilot

More Related Videos

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.9K

Related Experiment Videos

Last Updated: May 4, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

1.3K
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.9K

Area of Science:

  • Equine Science
  • Artificial Intelligence Applications

Background:

  • Artificial intelligence (AI) platforms are increasingly utilized for equine information retrieval.
  • These platforms synthesize data from diverse sources, often without differentiating between factual information and opinion.

Purpose of the Study:

  • To evaluate the accuracy and quality of AI-generated responses to equine-related queries.
  • To test the hypothesis that AI platforms excel at basic equine questions but falter on complex subjects.

Main Methods:

  • Forty equine-related questions were developed across five categories: general care, facilities, nutrition, genetics, and reproduction.
  • Questions were classified by difficulty (beginner, intermediate, advanced, trending) and posed to three AI platforms: ChatGPT, Microsoft Copilot, and ExtensionBot.
  • Responses were scored on accuracy, relevance, thoroughness, and source quality (maximum 20 points each).

Main Results:

  • AI platform performance varied significantly by question difficulty, topic, and platform.
  • ChatGPT and Microsoft Copilot demonstrated higher accuracy and relevance compared to ExtensionBot.
  • Intermediate-level questions received the highest overall scores, while complex topics presented challenges for AI accuracy and thoroughness.

Conclusions:

  • AI platforms can serve as supplementary resources for equine information but do not currently match the expertise of Equine Extension Specialists.
  • AI performance is inconsistent, particularly when addressing intricate equine subjects, highlighting areas for improvement.