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.
翻译：在科学出版中,要求作者建议一些审评员自己编写稿件,这越来越常见。然后出现的问题是:发现友好的审评员需要多少份提交书?为了回答这个问题,我们提出了一个代理模拟(单盲)同侪审查,然后是巴伊西亚对建议审评员的分类。为了降低对可能提交件数量的限制,我们创建了一个乐观的简单模式,让我们能够更方便地推断审查员的友好程度。尽管这一模式具有乐观的条件,但我们发现需要数百份提交书才能将即使是一个小的审查员子集分类。因此,在现实条件下,这种模拟几乎是不可能的。这确保同侪审查制度足够强大,能够让作者提出自己的审评员。
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