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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy
|
|---|---|
| Published in |
Genome Medicine, January 2019
|
| DOI | 10.1186/s13073-019-0616-z |
| Pubmed ID | |
| Authors |
Roddy Walsh, Francesco Mazzarotto, Nicola Whiffin, Rachel Buchan, William Midwinter, Alicja Wilk, Nicholas Li, Leanne Felkin, Nathan Ingold, Risha Govind, Mian Ahmad, Erica Mazaika, Mona Allouba, Xiaolei Zhang, Antonio de Marvao, Sharlene M. Day, Euan Ashley, Steven D. Colan, Michelle Michels, Alexandre C. Pereira, Daniel Jacoby, Carolyn Y. Ho, Kate L. Thomson, Hugh Watkins, Paul J. R. Barton, Iacopo Olivotto, Stuart A. Cook, James S. Ware |
X Demographics
The data shown below were collected from the profiles of 30 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 Kingdom | 8 | 27% |
| Spain | 3 | 10% |
| Netherlands | 3 | 10% |
| United States | 3 | 10% |
| Australia | 2 | 7% |
| Argentina | 1 | 3% |
| Russia | 1 | 3% |
| Unknown | 9 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 47% |
| Scientists | 13 | 43% |
| Practitioners (doctors, other healthcare professionals) | 3 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 128 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 18% |
| Researcher | 18 | 14% |
| Other | 12 | 9% |
| Student > Master | 12 | 9% |
| Student > Bachelor | 10 | 8% |
| Other | 25 | 20% |
| Unknown | 28 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 39 | 30% |
| Biochemistry, Genetics and Molecular Biology | 34 | 27% |
| Agricultural and Biological Sciences | 7 | 5% |
| Computer Science | 3 | 2% |
| Engineering | 3 | 2% |
| Other | 11 | 9% |
| Unknown | 31 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 14 June 2020.
All research outputs
#2,169,954
of 25,481,734 outputs
Outputs from Genome Medicine
#473
of 1,591 outputs
Outputs of similar age
#50,304
of 448,012 outputs
Outputs of similar age from Genome Medicine
#11
of 19 outputs
Altmetric has tracked 25,481,734 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,591 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.7. This one has gotten more attention than average, scoring higher than 70% 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 448,012 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 88% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.