Science is built upon scholarship consensus that changes over time. This raises the question of how revolutionary theories and assumptions are evaluated and accepted into the norm of science as the setting for the next science. Using two recently proposed metrics, we identify the novel paper with high atypicality, which models how research draws upon unusual combinations of prior research in crafting their own contributions, and evaluate recognition to novel papers by citation and disruption, which captures the degree to which a research article creates a new direction by eclipsing citations to the prior work it builds upon. Only a small fraction of papers (2.3%) are highly novel, and there are fewer novel papers over time, with a nearly threefold decrease from 3.9% in 1970 to 1.4% in 2000. A highly novel paper indeed has a much higher chance (61.3%) to disrupt science than conventional papers (36.4%), but this recognition only comes from a distant future as reflected in citations, and it typically takes 10 years or longer for the disruption score of a paper to stabilize. In comparison, only nearly 20% of scholars survived in academia over this long period, measured in publications. We also provide the first computational model reformulating atypicality as the distance across the latent knowledge spaces learned by neural networks, as a proxy to the socially agreed relevance between distinct fields of scientific knowledge. The evolution of this knowledge space characterizes how yesterdays novelty forms todays scientific conventions, which condition the novelty--and surprise--of tomorrows breakthroughs. This computational model may be used to inform science policy that aims to recognize and cultivate novelty, so as to mitigate the conflict between individual career success and collective advance in science and direct human creativity to the unknown frontier of scientific knowledge.
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