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  5. Guidance on Uncertainty Analysis in Scientific Assessments
 
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Guidance on Uncertainty Analysis in Scientific Assessments

Author(s)
Benford, Diane  
Halldorsson, Thorhallur  
Jeger, Michael John  
More, Simon John  
et al.  
Uri
http://hdl.handle.net/10197/10105
Date Issued
2018-01-24
Date Available
2019-04-24T08:49:25Z
Abstract
Uncertainty analysis is the process of identifying limitations in scientific knowledge and evaluating their implications for scientific conclusions. It is therefore relevant in all EFSA's scientific assessments and also necessary, to ensure that the assessment conclusions provide reliable information for decision-making. The form and extent of uncertainty analysis, and how the conclusions should be reported, vary widely depending on the nature and context of each assessment and the degree of uncertainty that is present. This document provides concise guidance on how to identify which options for uncertainty analysis are appropriate in each assessment, and how to apply them. It is accompanied by a separate, supporting opinion that explains the key concepts and principles behind this Guidance, and describes the methods in more detail.
Type of Material
Journal Article
Publisher
Wiley
Journal
EFSA Journal
Volume
16
Issue
1
Start Page
e05123
Copyright (Published Version)
2018 European Food Safety Authority
Subjects

Uncertainty analysis

Scientific assessment...

Guidance

DOI
10.2903/j.efsa.2018.5123
Language
English
Status of Item
Peer reviewed
ISSN
1831-4732
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
No Thumbnail Available
Name

Committee_et_al-2018-EFSA_Journal-2.pdf

Size

3.3 MB

Format

Adobe PDF

Checksum (MD5)

9e6b8816ba6bd989ece1e061baf3dd95

Owning collection
Veterinary Medicine Research Collection
Mapped collections
CVERA Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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