Can predicting an article's success change science? [Also see Report by Wang et al.] The massive growth of global research activity in recent years has spurred studies exploring how productive this expansion has been and what the future may hold. Although the creativity and serendipity of individual discoveries will remain difficult to model, quantitative research has revealed regularities in the rates of discovery and the outcome of published findings over time (1). Some of these studies demonstrate that innovation has been decreasing, which may reflect the output of a scientific enterprise whose system of input has supported the pursuit of research focused on “low-hanging fruit” (2). Coincident with this decline has been the recent global recession, a circumstance that called for accountability of economic and social returns from public investments in research (3). There is now a great demand for insight into how the system of science works. On page 127 of this issue, Wang et al. (4) offer one approach to assess, and perhaps even augment, scientific productivity.
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