Why is image integrity a problem?
Academic institutions recognize the importance of maintaining the highest standard of image integrity in their scientific publications. However, image issues such as reuse from published manuscripts, duplication and reuse within a manuscript, alteration and manipulation, and even AI-generated images remain widespread in academic publishing.
It's estimated that about one in three life sciences manuscripts submitted for publication are flagged for some kind of image-related issue. These problems are often unintentionally overlooked because issues are very difficult to spot with the naked eye. As a result, academic institutions are at risk of submitting manuscripts with image inaccuracies.
Many institutional stakeholders experience this challenge. Anyone — from presidents and deans for research and integrity, to heads of department and technology purchasing officers in libraries and resource centers — are all partners in integrity protection.
What are the consequences?
When investigating image integrity errors, we typically find that most turn out to be honest mistakes. While unintentional, failure to identify these breaches prior to submission for publication can severely damage an institution's reputation.
If an article is published with unresolved image issues, it might be identified and highlighted by peers in the academic community, through social media or on platforms like PubPeer.
Reports of issues can lead to very costly investigations and retractions. Misconduct investigations can cost anywhere up to one million dollars. As well as the cost, retractions cause enduring damage, not just to the individual researcher/s, but to the entire institution's reputation. This can significantly impair the researcher or institution’s ability to obtain funding in the future.
How does Proofig AI benefit research institutions?
Proofig AI was created with research teams and institutions in mind. The technology arose out of a deep understanding of the need for accuracy in scientific publication and a great motivation to support institutions in showcasing their highest quality of research.
Proofig AI is the ultimate smart solution that:
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Seamlessly integrates into a researcher’s existing pre-submission process to automate image checks.
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Identifies and analyzes sub-images, flagging potential errors to help researchers address and prevent issues before manuscript submission.
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Supports the manuscript submission protocol for researchers, departments, and entire institutions prior to submission, preventing the risk of mistakes and potential manuscript rejection.
Researchers and their institutions benefit from:
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Automatic and Fast Analysis: Proofig AI can analyze a large number of images quickly, providing detailed reports in minutes.
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Comprehensive Detection: The system detects a wide range of issues, from plagiarism and duplication to intricate manipulations.
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Considerable Time and Effort Savings: Minimizes the risk of post-publication critiques, saving valuable time and resources for research teams and departments.
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Confidential and Secure: All analyses are conducted on private, secure servers, ensuring the confidentiality of the research data.
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Integration with Workflow: Proofig AI seamlessly integrates into the existing pre-submission process, reducing the risk of post-publication critiques and retractions.
By utilizing these advanced capabilities, Proofig AI ensures that research institutions can maintain the highest standards of image integrity in their scientific publications.
How does it work?
Proofig AI leverages advanced machine learning techniques and an extensive database to ensure the integrity of scientific images by identifying various forms of image issues.
Researchers can check their manuscript, confidentially and automatically, in four simple steps:
1. Upload Your Manuscript
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Researchers begin by uploading their PDF manuscript to the Proofig platform. The system extracts all images and sub-images from the manuscript for analysis.
2. Analyze for Integrity Issues
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Proofig AI analyzes the manuscript for multiple types of image issues:
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Detection of Reuse from Published Manuscripts: By accessing PubMed’s Source database, which contains tens of millions of images, Proofig can identify reused sub-images, commonly known as plagiarism.
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Duplication and Reuse Within a Manuscript: Proofig identifies duplication or reuse of sub-images within the same manuscript. This includes detecting instances of scaling, rotation, flipping, full and partial overlap, ensuring each image is unique.
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Alteration and Manipulation: The system detects alterations or manipulations within a single sub-image, such as cloning, editing, deletion, and splicing, ensuring the authenticity of each sub-image.
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Detection of AI-Generated Images: Proofig AI identifies images created by the most widely used AI model. Proofig is committed to continually evolving and expanding its feature set to include new models, ensuring we stay ahead in the race to protect scientific integrity. Take Our Quiz To Test Yourself
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3. Validate and Review Results
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Researchers can check the detected sub-images and validate the results. They can then review any suspected issues flagged by Proofig AI.
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The system highlights suspected integrity issues, allowing researchers to add only relevant findings to the final report. Proofig also provides advanced further investigation tools to help users make well-informed decisions.
4. Generate a Comprehensive Report
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Proofig AI processes the selections and produces a comprehensive report in minutes. The report includes both a page view of the suspected issue and a detailed view of each confirmed issue.
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The report helps in ensuring the integrity of the scientific images before submission.
Data Privacy and Security
At Proofig, we prioritize the privacy and security of our users' data. We want to make it unequivocally clear that:
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Training Data: Our system is trained exclusively using material we have developed and open-source content designated for commercial use, ensuring compliance with legal and ethical standards.
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User Data: We do not use any data from user-uploaded manuscripts to train our models or algorithms. User-uploaded data is analyzed solely to detect image integrity issues within the submitted manuscript and generate the corresponding report.
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Confidentiality: All analyses are conducted on private, secure servers. Your manuscripts and reports remain fully confidential and are not used for any other purposes.
By adhering to these strict data privacy and security protocols, Proofig ensures that your data is protected while maintaining the highest standards of image integrity analysis.