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Infectious bursal disease virus: predicting viral pathotype using machine learning models focused on early changes in total blood cell counts

Overview of attention for article published in Veterinary Research, October 2023
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 X user

Readers on

mendeley
2 Mendeley
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Title
Infectious bursal disease virus: predicting viral pathotype using machine learning models focused on early changes in total blood cell counts
Published in
Veterinary Research, October 2023
DOI 10.1186/s13567-023-01222-5
Pubmed ID
Authors

Annonciade Molinet, Céline Courtillon, Stéphanie Bougeard, Alassane Keita, Béatrice Grasland, Nicolas Eterradossi, Sébastien Soubies

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 50%
Lecturer > Senior Lecturer 1 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 50%
Agricultural and Biological Sciences 1 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 31 October 2023.
All research outputs
#17,302,400
of 25,394,764 outputs
Outputs from Veterinary Research
#837
of 1,338 outputs
Outputs of similar age
#193,923
of 357,651 outputs
Outputs of similar age from Veterinary Research
#14
of 29 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,338 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 27th percentile – i.e., 27% 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 357,651 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.