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Ability of non-linear mixed models to predict growth in laying hens

Overview of attention for article published in Revista Brasileira de Zootecnia, November 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#10 of 351)
  • High Attention Score compared to outputs of the same age (82nd percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
14 Mendeley
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Title
Ability of non-linear mixed models to predict growth in laying hens
Published in
Revista Brasileira de Zootecnia, November 2014
DOI 10.1590/s1516-35982014001100003
Authors

Luis Fernando Galeano-Vasco, Mario Fernando Cerón-Muñoz, William Narváez-Solarte

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 7%
Unknown 13 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 43%
Student > Doctoral Student 3 21%
Student > Master 2 14%
Unspecified 1 7%
Other 1 7%
Other 1 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 50%
Veterinary Science and Veterinary Medicine 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Unspecified 1 7%
Unknown 4 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 09 June 2023.
All research outputs
#4,370,146
of 25,374,917 outputs
Outputs from Revista Brasileira de Zootecnia
#10
of 351 outputs
Outputs of similar age
#47,894
of 273,823 outputs
Outputs of similar age from Revista Brasileira de Zootecnia
#1
of 2 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 351 research outputs from this source. They receive a mean Attention Score of 2.0. This one has done particularly well, scoring higher than 97% of its peers.
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 273,823 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them