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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Validating and automating learning of cardiometabolic polygenic risk scores from direct-to-consumer genetic and phenotypic data: implications for scaling precision health research
|
|---|---|
| Published in |
Human Genomics, September 2022
|
| DOI | 10.1186/s40246-022-00406-y |
| Pubmed ID | |
| Authors |
Arturo Lopez-Pineda, Manvi Vernekar, Sonia Moreno-Grau, Agustin Rojas-Muñoz, Babak Moatamed, Ming Ta Michael Lee, Marco A. Nava-Aguilar, Gilberto Gonzalez-Arroyo, Kensuke Numakura, Yuta Matsuda, Alexander Ioannidis, Nicholas Katsanis, Tomohiro Takano, Carlos D. Bustamante |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Mexico | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 15% |
| Student > Master | 4 | 15% |
| Student > Ph. D. Student | 2 | 8% |
| Professor > Associate Professor | 2 | 8% |
| Professor | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 10 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 12% |
| Medicine and Dentistry | 3 | 12% |
| Computer Science | 3 | 12% |
| Unspecified | 2 | 8% |
| Agricultural and Biological Sciences | 2 | 8% |
| Other | 3 | 12% |
| Unknown | 10 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 15 September 2022.
All research outputs
#15,106,315
of 25,392,582 outputs
Outputs from Human Genomics
#309
of 564 outputs
Outputs of similar age
#190,092
of 432,719 outputs
Outputs of similar age from Human Genomics
#7
of 18 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 44th percentile – i.e., 44% 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 432,719 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.