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CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

Overview of attention for article published in Genome Medicine, August 2020
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  • Average Attention Score compared to outputs of the same age

Mentioned by

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4 X users

Citations

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30 Dimensions

Readers on

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71 Mendeley
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Title
CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations
Published in
Genome Medicine, August 2020
DOI 10.1186/s13073-020-00775-w
Pubmed ID
Authors

Shuang Li, K. Joeri van der Velde, Dick de Ridder, Aalt D. J. van Dijk, Dimitrios Soudis, Leslie R. Zwerwer, Patrick Deelen, Dennis Hendriksen, Bart Charbon, Marielle E. van Gijn, Kristin Abbott, Birgit Sikkema-Raddatz, Cleo C. van Diemen, Wilhelmina S. Kerstjens-Frederikse, Richard J. Sinke, Morris A. Swertz

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 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 13%
Student > Master 8 11%
Student > Bachelor 5 7%
Other 5 7%
Student > Postgraduate 5 7%
Other 11 15%
Unknown 28 39%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 27 38%
Medicine and Dentistry 8 11%
Agricultural and Biological Sciences 4 6%
Computer Science 2 3%
Mathematics 1 1%
Other 1 1%
Unknown 28 39%
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 24 August 2020.
All research outputs
#14,717,488
of 23,577,761 outputs
Outputs from Genome Medicine
#1,295
of 1,467 outputs
Outputs of similar age
#223,440
of 400,684 outputs
Outputs of similar age from Genome Medicine
#19
of 24 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.9. This one is in the 10th percentile – i.e., 10% 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 400,684 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 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.