  Reviewing the literature to understand relevant threads of past work is a
critical part of research and vehicle for learning. However, as the scientific
literature grows the challenges for users to find and make sense of the many
different threads of research grow as well. Previous work has helped scholars
to find and group papers with citation information or textual similarity using
standalone tools or overview visualizations. Instead, in this work we explore a
tool integrated into users' reading process that helps them with leveraging
authors' existing summarization of threads, typically in introduction or
related work sections, in order to situate their own work's contributions. To
explore this we developed a prototype that supports efficient extraction and
organization of threads along with supporting evidence as scientists read
research articles. The system then recommends further relevant articles based
on user-created threads. We evaluate the system in a lab study and find that it
helps scientists to follow and curate research threads without breaking out of
their flow of reading, collect relevant papers and clips, and discover
interesting new articles to further grow threads.
