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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra
|
|---|---|
| Published in |
BMC Bioinformatics, January 2023
|
| DOI | 10.1186/s12859-022-05128-5 |
| Pubmed ID | |
| Authors |
Emmanuel P. Mwanga, Doreen J. Siria, Joshua Mitton, Issa H. Mshani, Mario González-Jiménez, Prashanth Selvaraj, Klaas Wynne, Francesco Baldini, Fredros O. Okumu, Simon A. Babayan |
X Demographics
The data shown below were collected from the profiles of 40 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 | 10 | 25% |
| United States | 3 | 8% |
| Tanzania, United Republic of | 3 | 8% |
| Spain | 2 | 5% |
| Germany | 1 | 3% |
| Benin | 1 | 3% |
| Sweden | 1 | 3% |
| Burkina Faso | 1 | 3% |
| Ireland | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 17 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 21 | 53% |
| Scientists | 13 | 33% |
| Practitioners (doctors, other healthcare professionals) | 5 | 13% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 14% |
| Researcher | 4 | 11% |
| Lecturer | 2 | 6% |
| Professor | 2 | 6% |
| Student > Ph. D. Student | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 19 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 11% |
| Agricultural and Biological Sciences | 3 | 8% |
| Medicine and Dentistry | 2 | 6% |
| Engineering | 2 | 6% |
| Chemical Engineering | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 21 | 58% |
Attention Score in Context
This research output has an Altmetric Attention Score of 84. 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 06 December 2023.
All research outputs
#492,958
of 24,953,268 outputs
Outputs from BMC Bioinformatics
#21
of 7,615 outputs
Outputs of similar age
#11,438
of 469,552 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 128 outputs
Altmetric has tracked 24,953,268 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,615 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 99% 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 469,552 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 128 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.