Evidence map›Paper›PMID 42713314›Full record

ArticleTranslational animal science2026

Evaluation of large language model performance in translating dairy-related content.

Anay D Ravelo, Daniela G Carranza, Kaitlyn A Lutz, Wolfgang Heuwieser

Abstract read
In one paragraph

Article in Translational animal science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Anay D RaveloDepartment of Population Medicine and Diagnostic Sciences, Cornell University, Ithaca, NY 14850, United States.ORCID https://orcid.org/0000-0002-6583-4271
Daniela G CarranzaCornell Cooperative Extension, Cornell University, Ithaca, NY 14850, United States.
Kaitlyn A LutzCornell Cooperative Extension, Cornell University, Ithaca, NY 14850, United States.
Wolfgang HeuwieserDepartment of Population Medicine and Diagnostic Sciences, Cornell University, Ithaca, NY 14850, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence's ability to translate dairy-related texts from English to Spanish has not been well described in agriculture. This study aimed to determine the accuracy and comprehensibility of dairy-related translated text generated with ChatGPT (GPT-4o) and to determine the text's appropriateness for a dairy employee. Eight dairy udder health and stockmanship-related English texts were gathered from extension and university websites for translation. Four texts were summaries of 260 words or less and the other four texts were procedure lists with 8 steps. The texts were translated with a large language model (ChatGPT-4o) and displayed in a side-by-side presentation. The presentations were sent to 23 reviewers with a rubric for evaluation of accuracy, comprehensibility, and perception of the translation. Additionally, the reviewers were asked to evaluate if the translations were suitable to be shared with dairy employees. Overall, reviewers "Strongly agreed" or "Agreed" that the texts were accurately translated, including technical terms, and that the main idea of the text was correctly reproduced. They also "Strongly agreed" or "Agreed" that the translation was easy to understand, flowed naturally, was clear and coherent, and there was consistent translation of phrases that were repeated. Additionally, reviewers believed that there were "None" or "Few" instances where the meaning of the text is unclear due to the translation. Finally, the reviewers mostly agreed that they would present the translations to dairy employees. Thus, ChatGPT (GPT-4o) can accurately and comprehensibly translate dairy-related text. However, it is important to still have oversight and review the output.

Indexed as

artificial intelligenceEnglishSpanishstockmanshipudder health

Identifiers

PMID42713314
PMCPMC13553073

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.