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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Fast and scalable neural embedding models for biomedical sentence classification
|
|---|---|
| Published in |
BMC Bioinformatics, December 2018
|
| DOI | 10.1186/s12859-018-2496-4 |
| Pubmed ID | |
| Authors |
Asan Agibetov, Kathrin Blagec, Hong Xu, Matthias Samwald |
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 % |
|---|---|---|
| France | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 20% |
| Student > Ph. D. Student | 7 | 14% |
| Researcher | 5 | 10% |
| Lecturer | 4 | 8% |
| Student > Doctoral Student | 3 | 6% |
| Other | 12 | 24% |
| Unknown | 9 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 22 | 44% |
| Social Sciences | 3 | 6% |
| Engineering | 3 | 6% |
| Medicine and Dentistry | 3 | 6% |
| Agricultural and Biological Sciences | 3 | 6% |
| Other | 7 | 14% |
| Unknown | 9 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 February 2020.
All research outputs
#3,667,045
of 23,120,280 outputs
Outputs from BMC Bioinformatics
#1,320
of 7,330 outputs
Outputs of similar age
#81,515
of 436,262 outputs
Outputs of similar age from BMC Bioinformatics
#39
of 206 outputs
Altmetric has tracked 23,120,280 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,330 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 done well, scoring higher than 81% 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 436,262 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 206 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.