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Distributed peer review enhanced with natural language processing and machine learning

机译：分布式同行评审随着自然语言处理和机器学习而增强

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摘要

While ancient scientists often had patrons to fund their work, peer review of proposals for the allocation of resources is a foundation of modern science. A very common method is that proposals are evaluated by a small panel of experts (due to logistics and funding limitations) nominated by the grant-giving institutions. The expert panel process introduces several issues, most notably the following: (1) biases may be introduced in the selection of the panel and (2) experts have to read a very large number of proposals. Distributed peer review promises to alleviate several of the described problems by distributing the task of reviewing among the proposers. Each proposer is given a limited number of proposals to review and rank. We present the result of an experiment running a machine-learning-enhanced distributed peer-review process for allocation of telescope time at the European Southern Observatory. In this work, we show that the distributed peer review is statistically the same as a 'traditional' panel, that our machine-learning algorithm can predict expertise of reviewers with a high success rate, and that seniority and reviewer expertise have an influence on review quality. The general experience has been overwhelmingly praised by the participating community (using an anonymous feedback mechanism).The European Southern Observatory trialled a distributed peer-review system-augmented by automated reviewer assignment-for its telescope time allocation process, finding that it worked as well as the standard process but resulted in a smaller burden on reviewers.
机译：虽然古代科学家经常有顾客为他们的工作提供资金，但对资源配置提案的同行审查是现代科学的基础。一种非常常见的方法是，由赠款机构提名的专家小组（由于物流和资金限制）评估提案。专家小组流程引入了几个问题，最值得注意的是：（1）可以在选择面板的选择中引入偏见，并且（2）专家必须阅读大量提案。分布式同行审查承诺通过分发审核人员之间的任务来缓解几个描述的问题。每个提议者都有有限数量的审查和排名。我们介绍了运行机器学习增强的分布式对等审查过程的实验结果，以便在欧洲南部天文台分配望远镜时间。在这项工作中，我们表明，分布式同行评审与“传统”小组统计相同，我们的机器学习算法可以预测具有高成功率的审稿人的专业知识，并且资历和审阅者专业知识对审查产生影响质量。参与社区（使用匿名反馈机制）的一般经验一直受到压倒性地称赞。欧洲南部天文台通过自动评审员分配试验分布式同行评审系统 - 为其望远镜时间分配过程而增强，发现它也有用作为标准过程，但导致审阅者负担较小。

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  • 来源
    《Nature Astronomy》 |2020年第7期|711-717|共7页
  • 作者

    Kerzendorf Wolfgang E.; Patat Ferdinando; Bordelon Dominic; van de Ven Glenn; Pritchard Tyler A.;

  • 作者单位

    Michigan State Univ Dept Phys & Astron E Lansing MI 48824 USA|NYU Ctr Cosmol & Particle Phys New York NY 10003 USA|Michigan State Univ Dept Computat Math Sci & Engn E Lansing MI 48824 USA;

    European Southern Observ Munich Germany;

    European Southern Observ Munich Germany;

    European Southern Observ Munich Germany|Univ Vienna Dept Astrophys Vienna Austria;

    NYU Ctr Cosmol & Particle Phys New York NY 10003 USA;

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