Separation of uncertainty and variability in quantitative microbial risk assessment models.

By M. Nauta. 2000

247 citations recorded by the source corpus.

Subfields: Biotechnology, Food Science

View Paper: https://www.semanticscholar.org/paper/929e735af73072f0dce0bbbde33cbb96f1c1c3a4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biotechnology

1. Yinphan Tsang
2. Fu‐Chun Wu
3. J. Sofos

In Food Science

1. Yinphan Tsang
2. Fu‐Chun Wu
3. J. Sofos

Citations in the corpus

• Second-order Monte Carlo uncertainty/variability analysis using correlated model parameters: application to salmonid embryo survival risk assessment (2004, methodology): “Therefore, it has been increasingly emphasized the need to separate uncertainty and variability in risk assessments (Hoffman and Hammonds, 1994; Frey and Rhodes, 1996; Rai and Krewski, 1998; Nauta, 2000; Mitchell and Csillag, 2001).”
• Improving the safety of fresh meat (2005, background): “Error related to uncertainty is error due to a lack of data, and this is an area where more research or more data can reduce the associated error in the developed exposure assessment model (Nauta, 2000; Poschet et al., 2003).”