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Bayesian latent class models to determine diagnostic sensitivities and specificities of two point of care rapid tests (Selma plus, Dipslide) for the detection of Streptococcus uberis associated with…

Overview of attention for article published in Frontiers in Veterinary Science, December 2022
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2 X users

Citations

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1 Dimensions

Readers on

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6 Mendeley
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Title
Bayesian latent class models to determine diagnostic sensitivities and specificities of two point of care rapid tests (Selma plus, Dipslide) for the detection of Streptococcus uberis associated with mastitis in dairy cows
Published in
Frontiers in Veterinary Science, December 2022
DOI 10.3389/fvets.2022.1062056
Pubmed ID
Authors

David Rediger, Marc André Butty, Sonja Kittl, Michèle Bodmer, Sonja Hartnack

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 17%
Researcher 1 17%
Student > Master 1 17%
Unknown 3 50%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 1 17%
Biochemistry, Genetics and Molecular Biology 1 17%
Chemistry 1 17%
Unknown 3 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 December 2022.
All research outputs
#18,825,900
of 23,330,477 outputs
Outputs from Frontiers in Veterinary Science
#4,292
of 6,538 outputs
Outputs of similar age
#298,319
of 436,355 outputs
Outputs of similar age from Frontiers in Veterinary Science
#251
of 492 outputs
Altmetric has tracked 23,330,477 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,538 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 436,355 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 492 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.