Signals Data Graph will power Alchemist Review’s reviewer recommender, enabling faster, more accurate results.
Through the collaboration, Hum aims to significantly enhance Alchemist Review’s reviewer matching capabilities.
The partnership will enable publishers to streamline the reviewer finding process while only selecting high-quality, trustworthy reviewers, strengthening the speed and integrity of the peer review process.
Signals will provide Hum with access to the Signals Data Graph, a network of over 100 million publications evaluated for quality and integrity, which enables rapid, complex analyses. The integration will support two crucial steps in the reviewer finding process: first, identifying a wide range of potential reviewers, and second, filtering, scoring and ranking reviewers. This service also includes Signals evaluations of publications that potential reviewers are identified from, which enables editors to select reviewers based on their criteria, supporting high-quality peer review.
Hum and Signals will also explore additional use cases that can leverage the Signal Data Graph to enhance Alchemist Review’s comprehensive manuscript analysis.
“The Signals Data Graph is already helping publishers solve their research integrity challenges, and we’re excited to work with Hum to extend its impact across the publishing workflow,” says Elliott Lumb, co-founder of Signals. “We’re looking forward to collaborating with another industry innovator to bring greater intelligence and trust into publishing workflows.”
“Finding reviewers is still a burning need for handling editors. We have a few tricks up our sleeve to help shorten the time to secure qualified reviewers, and a key one starts with the Signals Data Graph, says Dustin Smith, Co-Founder & CEO of Hum. “We hope to reduce reviewer finding to minutes and shave days or weeks off securing qualified reviewers.”
The reviewer recommender feature is out in limited beta with Alchemist Review customers in preparation for wide release.
About Signals
Signals combines network analysis, expert knowledge, and AI to build a detailed understanding of the world’s research and deliver transparent, dynamic evaluations to publishers and researchers. For more details, visit research-signals.com or contact us directly at hello@research-signals.com
About Hum
Hum is building the intelligence layer for publishers. Its Alchemist suite speeds operational decisions by turning content, metadata, audience, and integrity signals into realtime intelligence. If you’re interested in shortening the time from submission to review, reach out to Richard (richard@hum.works) or visit https://www.hum.works/review.