Novelty is an essential feature of creative ideas, yet the building blocks of new ideas are often embodied in existing knowledge. From this perspective, balancing atypical knowledge with conventional knowledge may be critical to the link between innovativeness and impact. Our analysis of 17.9 million papers spanning all scientific fields suggests that science follows a nearly universal pattern: The highest-impact science is primarily grounded in exceptionally conventional combinations of prior work yet simultaneously features an intrusion of unusual combinations. Papers of this type were twice as likely to be highly cited works. Novel combinations of prior work are rare, yet teams are 37.7% more likely than solo authors to insert novel combinations into familiar knowledge domains.

Papers or patents that cite past work of a particular age distribution double their chances of being a hit.

How existing technologies and ideas are recombined into new innovations remains an important question, particularly as the store of prior technology, art, and work expands at an increasing rate. Yet, methodologies for identifying effective recombinations remain a nascent area of research. This paper extends our previous work, which developed a network methodology for assessing a scientific article's recombinations of prior work. The methodology uses information from the entire co‐citation network of all papers recorded in the Web of Science to identify combinations of prior work that are conventional or atypical and then identifies the virtuous mix of conventional and atypical pairings associated with high impact work. Here, we summarize our prior method and findings, present new findings, and perform a case study application to the field of management science. First, the results show that despite an ever‐increasing frontier of possible new combinations of prior work, atypical combinations of prior work are becoming increasingly rare with time, while the distribution of conventional pairings is increasing with time. Second, our analyses show that with time the atypical pairings found in hit papers have a relatively stable mean rate at which they become conventional pairing. Nevertheless, the variance around the mean is growing significantly, which indicates that there is a greater tendency over time for novel pairings either to be virtually never used again or to become conventional pairings.