Springer Nature and Université Grenoble Alpes release free enhanced integrity software to tackle fake scientific papers
PySciDetect builds on the original SciDetect open source software, to identify fake research and data at the point of submission
London | Grenoble, 31 March 2022
Springer Nature today announces the release of PySciDetect, its next generation open source research integrity software to identify fake research. Developed in-house with Slimmer AI and released in collaboration with Dr Cyril Labbé from Université Grenoble Alpes, PySciDetect is available for all publishers and those within the academic community to download and use. PySciDetect builds on the original software SciDetect launched in 2015, in two new ways:
- It uses advances in AI technology to more accurately and quickly detect1 fake data and research at the point of submission;
- It is more compatible with modern IT infrastructures, and therefore accessible to a wider user group, as it has been written using the programming language Python2.
Volker Boeing, Vice President, Process and Content Management Springer Nature commented,
“Publisher’s play an important role in maintaining the integrity of research. As part of that commitment at Springer Nature, we continue to increase our focus on ensuring sound and reliable research practice supported by our increasing investment into investigative tools to address and prevent error, fake research content and misconduct. PySciDetect is an example of this. Although software is not intended to, nor should it, replace human evaluation and expert peer review, it provides an additional, quick and now more accurate way to identify fraudulent research and data within papers before acceptance.”
Since launch, SciDetect has been used by a number of publishers and members of the academic community. For Springer Nature, it has scanned over 3.8million journal articles and over 2.5milion book chapters. Available as open source software, PySciDetect expands on Springer Nature’s commitment to being an active partner to the community, supporting a collaborative effort to detect fraudulent scientific research and protect the integrity of the academic record.
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Footnotes:
[1] PySciDetect is able to detect smaller portions of fake text within an article, compared to its predecessor SciDetect, which could only detect larger portions of generated text.
[2] The new software was re-written and implemented by Slimmer.ai in collaboration with Springer Nature.
Notes to Editors:
How does PySciDetect work?
Integrated into the submission workflow, PySciDetect scans research to identify any text and/ or data that has been generated with fake paper generators and computer programs such as SCIgen. It does this by comparing the submitted research against a database of fake scientific papers by computing a similarity of a submitted paper related to a corpus of fraudulent papers. PySciDetect will then provide a report on the paper highlighting any suspicious content it has detected and indicate which parts of the document are genuine or not. PySciDetect is now written using the Python programme language, meaning it is now compatible with a wider range of IT infrastructures and thus much easier to be downloaded and integrated by other publishers and members of the academic community.
Who can use it?
It is available to download under a GNU General Public License V3, which means that it is available for the whole research and academic community to use. It can be accessed and downloaded here.
For over 175 years Springer Nature has been advancing discovery by providing the best possible service to the whole research community. We help researchers uncover new ideas, make sure all the research we publish is significant, robust and stands up to objective scrutiny, that it reaches all relevant audiences in the best possible format, and can be discovered, accessed, used, re-used and shared. We support librarians and institutions with innovations in technology and data; and provide quality publishing support to societies.
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Anchored in its territory, multidisciplinary and open to the international, Université Grenoble Alpes brings together the main public higher education institutions of Grenoble and Valence. In association with the national research organizations and the international research facilities present on its territory, it builds its innovation policy on a global scale. As a driving force for progress and a laboratory for initiatives, it collaborates with its many partners to accompany the evolution of society. Find out more about Université Grenoble Alpes here.
Slimmer AI is a European AI B2B venture studio. We believe in the power of AI to power people’s work. For 10+ years, Slimmer AI has led the way in applying machine learning to solve real-world problems, partnering with entrepreneurs and industry leaders to build innovative applied AI products and ventures. For more information go to Slimmer AI.
Sam Sule | Communications | Springer Nature
sam.sule@springernature.com
