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Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework

Overview of attention for article published in Genome Medicine, December 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

blogs
1 blog
twitter
4 X users

Citations

dimensions_citation
333 Dimensions

Readers on

mendeley
256 Mendeley
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Title
Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework
Published in
Genome Medicine, December 2019
DOI 10.1186/s13073-019-0690-2
Pubmed ID
Authors

Sarah E. Brnich, Ahmad N. Abou Tayoun, Fergus J. Couch, Garry R. Cutting, Marc S. Greenblatt, Christopher D. Heinen, Dona M. Kanavy, Xi Luo, Shannon M. McNulty, Lea M. Starita, Sean V. Tavtigian, Matt W. Wright, Steven M. Harrison, Leslie G. Biesecker, Jonathan S. Berg

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 256 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 256 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 48 19%
Student > Ph. D. Student 32 13%
Other 21 8%
Student > Master 20 8%
Student > Doctoral Student 12 5%
Other 35 14%
Unknown 88 34%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 89 35%
Medicine and Dentistry 23 9%
Agricultural and Biological Sciences 23 9%
Immunology and Microbiology 4 2%
Physics and Astronomy 3 1%
Other 18 7%
Unknown 96 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 22 August 2023.
All research outputs
#3,486,648
of 26,017,215 outputs
Outputs from Genome Medicine
#758
of 1,611 outputs
Outputs of similar age
#81,308
of 481,617 outputs
Outputs of similar age from Genome Medicine
#21
of 32 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,611 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one has gotten more attention than average, scoring higher than 52% 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 481,617 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 32 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.