Letter to the Editor in Response to Forristal et al.: Improving the Quality of Risk Assessments in Canada Using a Principle-Based Approach, Regulatory Toxicology and Pharmacology 50 (2008) 336–344

2009 ◽  
Vol 53 (2) ◽  
pp. 156-157
Author(s):  
Bette Meek
Keyword(s):  
Risk Assessments ◽  
Regulatory Toxicology ◽  
Letter To The Editor

scholarly journals Enlisting Supervised Machine Learning in Mapping Scientific Uncertainty Expressed in Food Risk Analysis

2017 ◽  
Vol 48 (3) ◽  
pp. 608-641 ◽  
Author(s):  
Akos Rona-Tas ◽  
Antoine Cornuéjols ◽  
Sandrine Blanchemanche ◽  
Antonin Duroy ◽  
Christine Martin
Keyword(s):  
Machine Learning ◽  
Food Safety ◽  
Supervised Machine Learning ◽  
Risk Assessments ◽  
Scientific Uncertainty ◽  
Empirical Measure ◽  
Taxonomic Structure ◽  
Safety Risk ◽  
Food Safety Risk

Recently, both sociology of science and policy research have shown increased interest in scientific uncertainty. To contribute to these debates and create an empirical measure of scientific uncertainty, we inductively devised two systems of classification or ontologies to describe scientific uncertainty in a large corpus of food safety risk assessments with the help of machine learning (ML). We ask three questions: (1) Can we use ML to assist with coding complex documents such as food safety risk assessments on a difficult topic like scientific uncertainty? (2) Can we assess using ML the quality of the ontologies we devised? (3) And, finally, does the quality of our ontologies depend on social factors? We found that ML can do surprisingly well in its simplest form identifying complex meanings, and it does not benefit from adding certain types of complexity to the analysis. Our ML experiments show that in one ontology which is a simple typology, against expectations, semantic opposites attract each other and support the taxonomic structure of the other. And finally, we found some evidence that institutional factors do influence how well our taxonomy of uncertainty performs, but its ability to capture meaning does not vary greatly across the time, institutional context, and cultures we investigated.

scholarly journals Reply to “Letter to the editor: In response to Gunnarsson et al. on improving the quality of exercise interventions”

2020 ◽  
Vol 319 (5) ◽  
pp. C908-C909
Author(s):  
Thomas P. Gunnarsson ◽  
Thomas S. Ehlers ◽  
Matteo Fiorenza ◽  
Michael Nyberg ◽  
Jens Bangsbo
Keyword(s):  
Exercise Interventions ◽  
Letter To The Editor

Letter to the Editor: Accurate Element Identification is the Core Requirement for a Microanalysis System

2006 ◽  
Vol 12 (4) ◽  
pp. 281-282
Author(s):  
Simon Burgess
Keyword(s):  
Qualitative Analysis ◽  
The Core ◽  
Letter To The Editor

We at Oxford Instruments were interested to read the article published in Microscopy and Microanalysis by Newbury (2005). Although our own views differ from those of Dr. Newbury in some respects, we do agree that this is an important matter. If this article generates an interest in the ability of a system and a user to accurately identify elements in a spectrum and encourages people to assess the quality of the qualitative analysis provided by a microanalysis system, then we believe this article has served a very useful purpose. After all, accurate element identification is the core requirement for a microanalysis system.

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