Springer Nature has announced 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.
Since launch, SciDetect has been used by a number of publishers and members of the academic community. For Springer Nature, it has scanned over a 3.8 million journal articles and over a 2.5 milion 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.
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.
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.
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