Science

New chart aims to assess the reliability and relevance of scientific journals

Ad Fontes Science is developing a two-axis system intended to help organisations judge the quality and usefulness of scientific publications.

New chart aims to assess the reliability and relevance of scientific journals
©Illustration AI Alistair Kerr / we-news.com

A new rating system for scientific journals is being developed to assess both the reliability of their claims and the usefulness of their interpretation, potentially giving libraries, researchers and artificial-intelligence developers a new way to examine scientific sources.

The Scientific Information Reliability Chart, or SIRC, is being introduced by Ad Fontes Science, a division of Ad Fontes Media. It is due to launch on 4 November during the 2026 Charleston Premiers sessions at the Charleston Conference.

Rather than reducing a publication to a single ranking, the proposed approach places journals on two axes. One is intended to capture the dependability of the science behind their claims; the other considers how effectively findings are interpreted for the communities they are meant to serve. The result is designed to show two separate questions: whether the underlying work is reliable, and whether its conclusions are presented and interpreted responsibly.

Two measures, several tests

Ad Fontes Science says reliability will be examined through seven dimensions. These include the design and quality of studies, the disclosure of financial and ethical information, and the clarity with which scientific claims are made. The proposed framework therefore looks beyond the reputation of a journal and towards features of the work it publishes and the way that work is communicated.

Relevance is to be assessed separately through five dimensions. These cover the expertise of authors, the originality of the contribution, any promotional emphasis, accountability to the relevant community and the way claims are moderated through peer scrutiny.

Part of assessmentExamples of factors considered
ReliabilityStudy design, study quality, financial and ethical disclosures, clarity of claims
RelevanceAuthor expertise, original contribution, promotional focus, community accountability, peer scrutiny

The distinction matters because a paper may address an important subject without providing strong evidence, while technically sound work may have limited relevance to a particular audience. By displaying the two judgements independently, SIRC is intended to offer more information than a simple list ordered from “best” to “worst”.

Assessment at publication level

The organisation says journal positions will be based on reviews of dozens of papers, carried out by professional analysts using consistent criteria. Individual article assessments would then be combined to create ratings for publications. That method makes the proposed chart a summary of sampled content rather than an assertion that every paper in a journal has the same standard.

The project is being led by managing directors Kent Anderson and Joy Moore. Anderson has worked in publishing roles connected with the New England Journal of Medicine, Science, JBJS and Pediatrics. Moore has held positions at Nature Publishing Group, Blackwell and Silverchair, while Ad Fontes Media founder and chief executive Vanessa Otero is also involved.

Possible uses beyond researchers

Ad Fontes Science identifies several potential applications. Libraries and consortia could use the assessments when managing collections and examining variation across their publishing portfolios. Publishers could draw on them when considering editorial strategy, while researchers might consult the ratings when deciding where to submit papers.

The proposed system could also be used by aggregators and AI developers assessing scientific material for licensing or training datasets. Journalists and practitioners are among the other groups identified as possible users when they need to evaluate the sources behind a scientific claim.

Its importance will ultimately depend on how the criteria are applied and how clearly the resulting ratings are explained. For now, SIRC is a framework in development: an attempt to make a complicated judgement visible by separating the strength of scientific claims from the relevance and quality of their interpretation.

Alistair Kerr
Alistair AI Science Editor online

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