论文标题
量化科学进化中的释放
Quantifying exaptation in scientific evolution
论文作者
论文摘要
重新发现某事的新功能可能与发现本身一样重要。 1982年，斯蒂芬·杰伊·古尔德（Stephen Jay Gould）和伊丽莎白·弗巴（Elisabeth Vrba）命名了这种现象，以描述生物进化过程中特定性状的功能的根本转移。尽管被认为是产生适应性创新，多样性和复杂特征的基本机制，但在生物进化问题之外量化了被量化的努力相对较少。我们认为，这个概念为表征科学创新的出现提供了一个有用的框架。本文探讨了源于其最初应用领域以外的其他领域的科学思想的用法引起的概念。特别是，我们采用归一化熵和一个逆参与率作为可观察到的，揭示和量化了被释放的概念。我们确定了杰出的独特模式，并揭示了显示这些模式的论文的特定示例。我们的方法是在科学进化的背景下逐步量化出口现象的第一步。
Rediscovering a new function for something can be just as important as the discovery itself. In 1982, Stephen Jay Gould and Elisabeth Vrba named this phenomenon Exaptation to describe a radical shift in the function of a specific trait during biological evolution. While exaptation is thought to be a fundamental mechanism for generating adaptive innovations, diversity, and sophisticated features, relatively little effort has been made to quantify exaptation outside the topic of biological evolution. We think that this concept provides a useful framework for characterising the emergence of innovations in science. This article explores the notion that exaptation arises from the usage of scientific ideas in domains other than the area that they were originally applied to. In particular, we adopt a normalised entropy and an inverse participation ratio as observables that reveal and quantify the concept of exaptation. We identify distinctive patterns of exaptation and expose specific examples of papers that display those patterns. Our approach represents a first step towards the quantification of exaptation phenomena in the context of scientific evolution.
