论文标题
发现友好的建议审稿人需要多少意见？
How many submissions does it take to discover friendly suggested reviewers?
论文作者
论文摘要
在科学出版中，要求作者建议一些审稿人自己的手稿，这越来越普遍。然后出现问题：发现友好的建议审稿人需要多少意见？为了回答这个问题，我们提出了基于代理的（单叶）同行评审的模拟，然后对建议的审稿人进行贝叶斯分类。为了对可能的提交数量设置下限，我们创建了一个乐观的简单模型，该模型应该使我们更容易地推断出审阅者的友好程度。尽管有这种模型的乐观条件，我们发现，即使是小型审阅者子集，也需要数百种提交的内容来对其进行分类。因此，在现实条件下，它几乎是不可行的。这样可以确保同行评审系统足够强大，可以允许作者建议自己的审稿人。
It is ever more common in scientific publishing to ask authors to suggest some reviewers for their own manuscripts. The question then arises: How many submissions does it take to discover friendly suggested reviewers? To answer this question, we present an agent-based simulation of (single-blinded) peer review, followed by a Bayesian classification of suggested reviewers. To set a lower bound on the number of submissions possible, we create a optimistically simple model that should allow us to more readily deduce the degree of friendliness of the reviewer. Despite this model's optimistic conditions, we find that one would need hundreds of submissions to classify even a small reviewer subset. Thus, it is virtually unfeasible under realistic conditions. This ensures that the peer review system is sufficiently robust to allow authors to suggest their own reviewers.
