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X Demographics
Mendeley readers
Attention Score in Context
Title |
A functional assay–based procedure to classify mismatch repair gene variants in Lynch syndrome
|
---|---|
Published in |
Genetics in Medicine, December 2018
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DOI | 10.1038/s41436-018-0372-2 |
Pubmed ID | |
Authors |
Mark Drost, Yvonne Tiersma, Bryony A. Thompson, Jane H. Frederiksen, Guido Keijzers, Dylan Glubb, Scott Kathe, Jan Osinga, Helga Westers, Lisa Pappas, Kenneth M. Boucher, Siska Molenkamp, José B. Zonneveld, Christi J. van Asperen, David E. Goldgar, Susan S. Wallace, Rolf H. Sijmons, Amanda B. Spurdle, Lene J. Rasmussen, Marc S. Greenblatt, Niels de Wind, Sean V. Tavtigian |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 33% |
Unknown | 4 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 67% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 44 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 9 | 20% |
Student > Bachelor | 6 | 14% |
Other | 6 | 14% |
Student > Ph. D. Student | 4 | 9% |
Student > Master | 2 | 5% |
Other | 3 | 7% |
Unknown | 14 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 11 | 25% |
Agricultural and Biological Sciences | 9 | 20% |
Medicine and Dentistry | 6 | 14% |
Computer Science | 1 | 2% |
Immunology and Microbiology | 1 | 2% |
Other | 1 | 2% |
Unknown | 15 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 58. 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 December 2018.
All research outputs
#739,089
of 25,837,817 outputs
Outputs from Genetics in Medicine
#194
of 2,970 outputs
Outputs of similar age
#16,410
of 450,417 outputs
Outputs of similar age from Genetics in Medicine
#6
of 71 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,970 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.1. This one has done particularly well, scoring higher than 93% 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 450,417 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.