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An algorithm for the identification of genetically modified animals

Overview of attention for article published in Trends in Biotechnology, May 2013
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3 X users

Citations

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19 Mendeley
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Title
An algorithm for the identification of genetically modified animals
Published in
Trends in Biotechnology, May 2013
DOI 10.1016/j.tibtech.2013.02.001
Pubmed ID
Authors

Flavio Forabosco, Fredrik L. Sundström, Lotta Rydhmer

Abstract

The diffusion of genetically modified (GM) animals has generated a demand for accurate and unique identification to assure compliance with relevant national and international legislation. Individual identification of GM animals is essential to improve safety and traceability, as well as to fulfill the present and future expectations of producers, consumers, and authorities.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 5%
Germany 1 5%
Unknown 17 89%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 6 32%
Researcher 3 16%
Other 2 11%
Student > Doctoral Student 2 11%
Student > Ph. D. Student 1 5%
Other 3 16%
Unknown 2 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 37%
Social Sciences 3 16%
Arts and Humanities 2 11%
Engineering 2 11%
Chemistry 1 5%
Other 1 5%
Unknown 3 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 30 April 2013.
All research outputs
#16,722,190
of 25,374,917 outputs
Outputs from Trends in Biotechnology
#2,598
of 2,856 outputs
Outputs of similar age
#124,979
of 204,329 outputs
Outputs of similar age from Trends in Biotechnology
#17
of 22 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,856 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one is in the 8th percentile – i.e., 8% 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 204,329 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.