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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method
|
|---|---|
| Published in |
Frontiers in Molecular Biosciences, July 2022
|
| DOI | 10.3389/fmolb.2022.952626 |
| Pubmed ID | |
| Authors |
Hao Li, Feiming Huang, Huiping Liao, Zhandong Li, Kaiyan Feng, Tao Huang, Yu-Dong Cai |
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 % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 25% |
| Student > Doctoral Student | 2 | 17% |
| Student > Postgraduate | 1 | 8% |
| Professor > Associate Professor | 1 | 8% |
| Unknown | 5 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 17% |
| Medicine and Dentistry | 2 | 17% |
| Agricultural and Biological Sciences | 1 | 8% |
| Immunology and Microbiology | 1 | 8% |
| Chemistry | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 5 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 11 August 2022.
All research outputs
#17,302,467
of 26,175,267 outputs
Outputs from Frontiers in Molecular Biosciences
#1,698
of 4,792 outputs
Outputs of similar age
#243,116
of 439,688 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#128
of 409 outputs
Altmetric has tracked 26,175,267 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,792 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 57% 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 439,688 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 409 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 60% of its contemporaries.