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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep learning with language models improves named entity recognition for PharmaCoNER
|
|---|---|
| Published in |
BMC Bioinformatics, December 2021
|
| DOI | 10.1186/s12859-021-04260-y |
| Pubmed ID | |
| Authors |
Cong Sun, Zhihao Yang, Lei Wang, Yin Zhang, Hongfei Lin, Jian Wang |
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 % |
|---|---|---|
| United States | 1 | 33% |
| France | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 5 | 20% |
| Researcher | 3 | 12% |
| Other | 2 | 8% |
| Student > Ph. D. Student | 2 | 8% |
| Student > Bachelor | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 9 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 5 | 20% |
| Computer Science | 4 | 16% |
| Agricultural and Biological Sciences | 2 | 8% |
| Business, Management and Accounting | 1 | 4% |
| Environmental Science | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 10 | 40% |
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 27 December 2021.
All research outputs
#15,030,956
of 23,885,338 outputs
Outputs from BMC Bioinformatics
#4,846
of 7,484 outputs
Outputs of similar age
#235,091
of 473,920 outputs
Outputs of similar age from BMC Bioinformatics
#110
of 148 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,484 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 473,920 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 148 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.