GUM关于开发和使用度量模型的指导

IF 0.8 4区 工程技术 Q4 CHEMISTRY, ANALYTICAL
Adriaan M. H. van der Veen, Maurice G. Cox, Antonio Possolo
{"title":"GUM关于开发和使用度量模型的指导","authors":"Adriaan M. H. van der Veen,&nbsp;Maurice G. Cox,&nbsp;Antonio Possolo","doi":"10.1007/s00769-022-01509-8","DOIUrl":null,"url":null,"abstract":"<div><p>The GUM suite of documents (Guide to the expression of uncertainty in measurement and related documents) has been expanded with the addition of a new guidance document describing the development and use of measurement models for obtaining a value for the measurand and an associated measurement uncertainty. The methods for estimating the measurand and evaluating measurement uncertainty in the GUM suite all hinge upon a measurement model that relates the measurand to a set of input quantities. Many users find the development of these models challenging, and so far little guidance has been made available for how to address this pervasive challenge. In this paper, we show how the new document takes the reader from the specification of the measurand through the steps needed to arrive at a complete measurement model, suitable for providing a value for the measurand and an associated uncertainty. An important intermediate stage in this process is the description of the measurement principle, as for many users of standardized test methods this principle is already described by a model. This “basic model” needs extension to include effects arising from the measurement, such as calibration, corrections to be applied, repeatability and reproducibility. The document also introduces statistical models, which recognise the dispersion of replicated observations of the same quantity while capturing the fact that all are informative about the true value of the measurand. JCGM GUM-6 is a valuable contribution to the GUM suite in that it provides a structured and flexible approach to the creation, validation, and use of measurement models.</p></div>","PeriodicalId":454,"journal":{"name":"Accreditation and Quality Assurance","volume":"27 5","pages":"295 - 297"},"PeriodicalIF":0.8000,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00769-022-01509-8.pdf","citationCount":"2","resultStr":"{\"title\":\"GUM guidance on developing and using measurement models\",\"authors\":\"Adriaan M. H. van der Veen,&nbsp;Maurice G. Cox,&nbsp;Antonio Possolo\",\"doi\":\"10.1007/s00769-022-01509-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The GUM suite of documents (Guide to the expression of uncertainty in measurement and related documents) has been expanded with the addition of a new guidance document describing the development and use of measurement models for obtaining a value for the measurand and an associated measurement uncertainty. The methods for estimating the measurand and evaluating measurement uncertainty in the GUM suite all hinge upon a measurement model that relates the measurand to a set of input quantities. Many users find the development of these models challenging, and so far little guidance has been made available for how to address this pervasive challenge. In this paper, we show how the new document takes the reader from the specification of the measurand through the steps needed to arrive at a complete measurement model, suitable for providing a value for the measurand and an associated uncertainty. An important intermediate stage in this process is the description of the measurement principle, as for many users of standardized test methods this principle is already described by a model. This “basic model” needs extension to include effects arising from the measurement, such as calibration, corrections to be applied, repeatability and reproducibility. The document also introduces statistical models, which recognise the dispersion of replicated observations of the same quantity while capturing the fact that all are informative about the true value of the measurand. JCGM GUM-6 is a valuable contribution to the GUM suite in that it provides a structured and flexible approach to the creation, validation, and use of measurement models.</p></div>\",\"PeriodicalId\":454,\"journal\":{\"name\":\"Accreditation and Quality Assurance\",\"volume\":\"27 5\",\"pages\":\"295 - 297\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s00769-022-01509-8.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accreditation and Quality Assurance\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00769-022-01509-8\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accreditation and Quality Assurance","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s00769-022-01509-8","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 2

摘要

GUM文件套件(测量不确定度表达指南和相关文件)已经扩展,增加了一个新的指导文件,描述了测量模型的开发和使用,以获得测量值和相关的测量不确定度。在GUM套件中,估计测量和评估测量不确定度的方法都依赖于一个测量模型,该模型将测量与一组输入量联系起来。许多用户发现这些模型的开发具有挑战性,到目前为止,关于如何解决这一普遍挑战的指导很少。在本文中,我们展示了新文档如何带领读者从测量的规范开始,并通过所需的步骤到达一个完整的测量模型,适合为测量和相关的不确定度提供一个值。这个过程中一个重要的中间阶段是测量原理的描述,因为对于许多标准化测试方法的用户来说,这个原理已经被模型描述了。这个“基本模型”需要扩展,以包括测量产生的影响,如校准、要应用的校正、可重复性和可再现性。该文件还介绍了统计模型,该模型识别相同数量的重复观测的离散性,同时捕获所有关于测量值的真实值的信息这一事实。JCGM GUM-6是对GUM套件的一个有价值的贡献,因为它为创建、验证和使用度量模型提供了一种结构化和灵活的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GUM guidance on developing and using measurement models

The GUM suite of documents (Guide to the expression of uncertainty in measurement and related documents) has been expanded with the addition of a new guidance document describing the development and use of measurement models for obtaining a value for the measurand and an associated measurement uncertainty. The methods for estimating the measurand and evaluating measurement uncertainty in the GUM suite all hinge upon a measurement model that relates the measurand to a set of input quantities. Many users find the development of these models challenging, and so far little guidance has been made available for how to address this pervasive challenge. In this paper, we show how the new document takes the reader from the specification of the measurand through the steps needed to arrive at a complete measurement model, suitable for providing a value for the measurand and an associated uncertainty. An important intermediate stage in this process is the description of the measurement principle, as for many users of standardized test methods this principle is already described by a model. This “basic model” needs extension to include effects arising from the measurement, such as calibration, corrections to be applied, repeatability and reproducibility. The document also introduces statistical models, which recognise the dispersion of replicated observations of the same quantity while capturing the fact that all are informative about the true value of the measurand. JCGM GUM-6 is a valuable contribution to the GUM suite in that it provides a structured and flexible approach to the creation, validation, and use of measurement models.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Accreditation and Quality Assurance
Accreditation and Quality Assurance 工程技术-分析化学
CiteScore
1.80
自引率
22.20%
发文量
39
审稿时长
6-12 weeks
期刊介绍: Accreditation and Quality Assurance has established itself as the leading information and discussion forum for all aspects relevant to quality, transparency and reliability of measurement results in chemical and biological sciences. The journal serves the information needs of researchers, practitioners and decision makers dealing with quality assurance and quality management, including the development and application of metrological principles and concepts such as traceability or measurement uncertainty in the following fields: environment, nutrition, consumer protection, geology, metallurgy, pharmacy, forensics, clinical chemistry and laboratory medicine, and microbiology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信