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Proofig for authors and researchers

The benefits of automated image integrity detection software for scientific writing

What is Proofig?

Proofig is an automated software we've developed that uses cutting-edge AI and computer vision for automatic identification of scientific image issues before publication.

 

Proofig can detect full duplications (include scaling or rotation), partial duplication or overlapping, alongside flipped images, rotations, cloning, and any of these issues combined.

Why is image integrity a problem?

While most researchers understand the importance of image integrity, such issues are prevalent in publishing. Around a third of life sciences manuscripts are flagged for image related issues (1). Image related issues are difficult to detect by a naked eye, making most researchers in life science at the risk of publishing manuscripts with image issues.

While image integrity issues are often unintentional, not using the appropriate tools to resolve them before publication can be detrimental to the researchers' reputation. Publishers may reject the paper without disclosing a reason.

Alternatively, if a paper is published with the image issues, others in the community may flag the issue, either on social media or PubPeer. This can lead to costly investigations and lasting reputational damage, making it much more difficult to gain funding, publish content in the future and progress in your scientific career.

How does Proofig benefit researchers?

Proofig was created by researchers, for researchers.

Proofig arose out of a deep understanding of the need for accuracy in scientific publication and a great motivation to support you in bringing your best work into the world.

Our software provides:

  • Accurate analysis of manuscripts, reducing human error

  • Automatic analysis of a large number of images in a manuscript, providing reports in minutes

  • Significant time and effort reduction through minimization of post-publication critique risk

All results are fully confidential — the system operates on a private, secure server

How does it work?

Proofig extracts images from papers and compares each image to itself, then to the rest of the images, in order to detect duplications or other anomalies. It also compares each flipped image with the other images in the uploaded files.

Check your manuscript, confidentially and automatically, in three simple steps:

  • Upload your PDF manuscript and submit it for sub-image detection. The system will leverage AI to analyze your manuscript and mark all sub-images within the figures.

  • Review the detected sub-images and validate the results, then submit the manuscript for integrity detection.

  • Review the suspected issues Proofig has flagged for you and add only relevant findings to the final report. The system will process your selections within minutes, and you’ll have the full report, which can be printed (PDF) or seen as-is within the system. The report will include both a page view of the suspected issue and a detailed view of each issue you confirmed.

Who are Proofig's clients?

Proofig’s clients include PIs and senior researchers in life sciences, as well as integrity role holders from top universities and prominent international publishers, such as AACR, SAGE Publishing, RSC, JCI, and Taylor & Francis.

Proofig has been quoted in Nature and by COPE as a leader in the field of image integrity.

Read more reviews from your peers here, then choose the package that best meets your needs.

photo of Professor Ofer Mandelboim.png

"Significant damage is caused by image duplication even when they are innocent mistakes. Therefore, I'm happy to provide my department with the peace of mind that comes with knowing our manuscripts' images have been properly verified pre-publication using Proofig, and only manuscripts with no mistakes will follow for publication".

Professor Ofer Mandelboim

Head of the Department of Immunology and Cancer Research

Hebrew University Faculty of Medicine, Israel

Hear what renowned editors & scientists are saying about Proofig

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