Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.
Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.
PLoS Biol. 2018 Apr 23;16(4):e2004299. doi: 10.1371/journal.pbio.2004299. eCollection 2018 Apr.
The current push for rigor and reproducibility is driven by a desire for confidence in research results. Here, we suggest a framework for a systematic process, based on consensus principles of measurement science, to guide researchers and reviewers in assessing, documenting, and mitigating the sources of uncertainty in a study. All study results have associated ambiguities that are not always clarified by simply establishing reproducibility. By explicitly considering sources of uncertainty, noting aspects of the experimental system that are difficult to characterize quantitatively, and proposing alternative interpretations, the researcher provides information that enhances comparability and reproducibility.
当前对严谨性和可重复性的推动是出于对研究结果信心的渴望。在这里,我们基于测量科学的共识原则,提出了一个系统的过程框架,以指导研究人员和评审人员评估、记录和减轻研究中不确定性的来源。所有的研究结果都存在相关的歧义,而仅仅通过建立可重复性并不总是能澄清这些歧义。通过明确考虑不确定性的来源,注意实验系统中难以定量描述的方面,并提出替代解释,研究人员提供了增强可比性和可重复性的信息。