ARTEMIS, from the ResearchHub Foundation, is an agentic AI peer review system built on large language and multi-modal models. The design premise: AI reviewers catch technical errors and statistical flaws better than humans; human reviewers judge relevance and context better than AI. So it does both, together.
Benefits & outcomes
AI outperformed humans at spotting technical and statistical errors in ResearchHub's own 200+ review sample.
Human reviewers stay in the loop for relevance and context.
Specialised agents for different aspects of scientific document auditing.
Notes & quotes
"We have observed from our own experiments (200+ AI peer review samples) that AI reviewers have capabilities that excel in domains such as detecting technical errors and statistical flaws, while human reviewers provide greater insight into the broader relevance and context of research."
Publisher / company: ResearchHub Foundation
Date of mention: 27/02/2025
Source: https://www.researchhub.com/post/3961/artemis-automated-review-and-trustworthy-evaluation-for-manuscripts-in-sciencebr?utm_source=scalene-peer-review.beehiiv.com&utm_medium=referral&utm_campaign=scalene-31-one-step-back-artemis-paint