You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep learning versus parametric and ensemble methods for genomic prediction of complex phenotypes
|
|---|---|
| Published in |
Genetics Selection Evolution, February 2020
|
| DOI | 10.1186/s12711-020-00531-z |
| Pubmed ID | |
| Authors |
Rostam Abdollahi-Arpanahi, Daniel Gianola, Francisco Peñagaricano |
X Demographics
The data shown below were collected from the profiles of 12 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 | 2 | 17% |
| Germany | 1 | 8% |
| France | 1 | 8% |
| India | 1 | 8% |
| United States | 1 | 8% |
| Australia | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 75% |
| Scientists | 2 | 17% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 169 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 15% |
| Student > Master | 25 | 15% |
| Researcher | 24 | 14% |
| Student > Doctoral Student | 10 | 6% |
| Student > Bachelor | 8 | 5% |
| Other | 25 | 15% |
| Unknown | 51 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 47 | 28% |
| Biochemistry, Genetics and Molecular Biology | 23 | 14% |
| Computer Science | 12 | 7% |
| Engineering | 4 | 2% |
| Environmental Science | 2 | 1% |
| Other | 17 | 10% |
| Unknown | 64 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 13 July 2020.
All research outputs
#5,409,395
of 25,387,668 outputs
Outputs from Genetics Selection Evolution
#139
of 821 outputs
Outputs of similar age
#108,765
of 384,401 outputs
Outputs of similar age from Genetics Selection Evolution
#9
of 15 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 821 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 82% 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 384,401 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 71% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.