A researcher at TalTech warns that scientific paper mills and artificially intelligent content generation are increasingly jeopardizing the trustworthiness of academic research. According to Anton Sokolov, the proliferation of these fabricated papers isn't fully captured by retraction rates, suggesting a significant hidden problem. These mills produce and sell fraudulent research papers, while AI tools can create plausible but inaccurate content, both contributing to a polluted scientific landscape. This contamination is now demonstrably affecting the results generated by Large Language Models (LLMs) when researchers use them for literature reviews or data synthesis. The issue raises concerns about the reliability of scientific findings and the potential for misinformation to spread within academic circles and beyond. Sokolov’s research highlights the need for better detection methods and preventative measures to safeguard research integrity in the face of these emerging threats.