Springer Nature unveils two new AI tools

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Chris Graf, Research Integrity Director at Springer Nature

Springer Nature is rolling out two new bespoke AI tools to support the identification of papers that contain AI-generated fake content and/or problematic images - two indicators of research integrity issues.

Developed with Slimmer AI Science division, which Springer Nature acquired in 2023, one tool, Geppetto, detects AI-generated content, a classic indication of paper mill activity.

Geppetto works by dividing the paper up into sections and uses its own algorithms to check the consistency of the text in each section. The sections are then given a score based on the probability that the text in them has been AI generated. The higher the score, the greater the probability of there being problems, initiating a human check by Springer Nature staff. The publisher says Geppetto is already responsible for identifying hundreds of fake papers soon after submission, preventing them from being published – and from taking up editors’ and peer reviewers’ time.

SnappShot, also developed in-house, is an AI-assisted image integrity analysis tool. Currently used to analyse PDF files containing gel and blot images and look for duplications in those image types – another known integrity problem within the industry – this will be expanded to cover additional image types and integrity problems and speed up checks on papers.

As with Geppetto, SnappShot does not make the decision on whether a submission should progress through to the next stage of the editorial process but provides a signal as to whether human assessment of the images is needed. The tool not only helps to avoid publishing duplicated or manipulated data, but also supports good feedback for authors on their figures, for example where figures have been inadvertently duplicated, encouraging higher standards of research practice and data management.

Commenting, Chris Graf, Research Integrity Director at Springer Nature, said: “The publishing industry faces a determined, malicious threat from paper mills or bad actors who submit fake papers containing fabricated data and we are determined that this content will not get through our systems. These attempts can have serious consequences for trust in science and investigating and resolving them can take up an enormous amount of time and resources.

“Our new tools, which we are constantly improving, are helping us to stay one step ahead of the fraudsters and ensure that the research we published is robust and can be trusted to be used and built on.”

 

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