In a rapidly changing technological world, ensuring research and publications are accurate, trustworthy and ethical is more important than ever before. The evolution of generative AI and LLMs has significantly shifted longstanding paradigms in scientific publishing. Coupled with the emergence of systematic challenges to research integrity such as paper mills, it is essential that publishers take steps to protect the scientific record. 

Consequently, many publishers have created dedicated Research Integrity roles to manage these issues but what do these roles actually entail and how are these cases investigated and eventually resolved? While many people are aware of research integrity as a concept, the processes that underpin investigations and resolutions can often be opaque.

Many publishers are now also harnessing these new technologies and incorporating them into integrity workflows. Signals Manuscript Checks is a tool that provides automated and transparent evaluations of manuscripts to identify research integrity issues. Signals combines network analysis, expert knowledge, and AI to deliver these evaluations within editorial workflows, and it also enables AI-supported investigations of manuscripts through Sleuth AI, Signals' AI-powered research integrity assistant. By identifying potential integrity issues accurately and efficiently, Signals helps journal teams protect the scientific record and ensure that only trustworthy research reaches the community.