Identity & Access Management Architect
Weill Cornell Medicine
In academic settings, staff are tasked with compiling scholarly publications—a challenge intensified by common author names and varied affiliations. While ORCID offers some respite for author disambiguation, it doesn’t encompass all institutional needs. ReCiter fills this gap as an open-source, machine-learning tool that identifies individual-authored publications in PubMed by harnessing institution-specific identity data. Streamlining the identification process and enabling real-time updates on new publications, ReCiter is integral to a broader publication management ecosystem. This system amalgamates external data, refines records, gives ML-guided authorship recommendations, standardizes data, and provides a user-friendly interface for feedback, comprehensive reports, and record syndication. ReCiter’s functionality goes beyond what existing products offer including inferences regarding author position and one-click generation of bibliometric reports and the ability to output Word documents with the target author name bolded, and data such as NIH metrics of impact and reported conflicts of interest. Such an infrastructure ensures institutions can efficiently manage diverse scholarly reporting and profiling needs.