Sentence examples for condemnation of data from inspiring English sources

First of all, let me be clear: the headline of this article is a reference to Pete Warden's post, and should be read in the same way - as a caution against blind acceptance, rather than the wholesale condemnation of data visualisation.

New approaches to animal disease surveillance, such as syndromic surveillance of condemnation data may be important for the timely identification of infectious animal and zoonotic disease events in the future.

"Parasitic liver" and pneumonic lung condemnations were used in this case study as these condemnation classes were a rich source of data.

A prospective system that incorporates the purposeful, standardized collection of partial condemnation data pertaining to organs of interest for disease surveillance could be validated with other health information.

Portion condemnations and whole carcass condemnation data have been previously described in the literature [ 20- 22], however, few reports of potential usages of these data for syndromic surveillance purposes have been implemented.

Overall, the results for both types of portion condemnation data demonstrate that as you increase the detail in the covariate adjustment information, the size of the cluster decreases.

The model-adjusted approach using the ratio of observed versus expected condemnations under the Poisson model would be more appropriate when utilizing relatively rare events, as in the case of abattoir condemnation data.

However, inherent characteristics of abattoir condemnation data can bias results from space-time cluster detection methods for disease surveillance, and may need to be accounted for using various adjustment methods.

Abattoir condemnation data show promise as a rich source of data for syndromic surveillance of both animal and zoonotic diseases.

These are important factors to consider when selecting portion condemnation designations for syndromic surveillance; a previous study by Thomas et al. [ 19], investigating the use of portion condemnations in market hogs, noted that the quality of data recording was poor for organs that were not considered to be economically important or a concern for food safety.

Principal component method such as MFA allowed the definition of a distance between condemned cattle based on several sets of categorical variables (demographic and condemnation data) through the computation of the Euclidean distance from the individual principal coordinates from MFA.