  The problem of identifying common concepts in the sciences and deciding when
new ideas have emerged is an open one. Metascience researchers have sought to
formalize principles underlying stages in the life-cycle of scientific
research, determine how knowledge is transferred between scientists and
stakeholders, and understand how new ideas are generated and take hold. Here,
we model the state of scientific knowledge immediately preceding new directions
of research as a metastable state and the creation of new concepts as
combinatorial innovation. We find that, through the combined use of natural
language clustering and citation graph analysis, we can predict the evolution
of ideas over time and thus connect a single scientific article to past and
future concepts in a way that goes beyond traditional citation and reference
connections.
