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 |
Developing a diagnostic method for latent tuberculosis infection using circulating miRNA
|
|---|---|
| Published in |
Translational Medicine Communications, December 2020
|
| DOI | 10.1186/s41231-020-00078-7 |
| Authors |
Shoji Hashimoto, Hong Zhao, Michiyo Hayakawa, Koichi Nakajima, Y-h Taguchi, Yoshiki Murakami |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Colombia | 1 | 25% |
| United States | 1 | 25% |
| Japan | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 2 | 22% |
| Student > Doctoral Student | 2 | 22% |
| Other | 1 | 11% |
| Lecturer > Senior Lecturer | 1 | 11% |
| Student > Ph. D. Student | 1 | 11% |
| Other | 1 | 11% |
| Unknown | 1 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Immunology and Microbiology | 2 | 22% |
| Medicine and Dentistry | 2 | 22% |
| Mathematics | 1 | 11% |
| Chemical Engineering | 1 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 11% |
| Other | 1 | 11% |
| Unknown | 1 | 11% |
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 09 March 2021.
All research outputs
#14,242,332
of 23,267,128 outputs
Outputs from Translational Medicine Communications
#32
of 83 outputs
Outputs of similar age
#262,157
of 508,706 outputs
Outputs of similar age from Translational Medicine Communications
#5
of 11 outputs
Altmetric has tracked 23,267,128 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 83 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has gotten more attention than average, scoring higher than 59% 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 508,706 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 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 54% of its contemporaries.