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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A multi-task CNN learning model for taxonomic assignment of human viruses
|
|---|---|
| Published in |
BMC Bioinformatics, June 2021
|
| DOI | 10.1186/s12859-021-04084-w |
| Pubmed ID | |
| Authors |
Haoran Ma, Tin Wee Tan, Kenneth Hon Kim Ban |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 9% |
| United States | 1 | 9% |
| Sweden | 1 | 9% |
| United Kingdom | 1 | 9% |
| Unknown | 7 | 64% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 64% |
| Scientists | 4 | 36% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 4 | 17% |
| Student > Master | 4 | 17% |
| Student > Bachelor | 2 | 9% |
| Professor | 2 | 9% |
| Researcher | 2 | 9% |
| Other | 3 | 13% |
| Unknown | 6 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 17% |
| Nursing and Health Professions | 3 | 13% |
| Engineering | 3 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 9% |
| Social Sciences | 2 | 9% |
| Other | 4 | 17% |
| Unknown | 5 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 05 June 2021.
All research outputs
#5,808,457
of 23,498,099 outputs
Outputs from BMC Bioinformatics
#2,088
of 7,400 outputs
Outputs of similar age
#123,172
of 449,028 outputs
Outputs of similar age from BMC Bioinformatics
#44
of 177 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 71% 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 449,028 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 72% of its contemporaries.
We're also able to compare this research output to 177 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.