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A transfer learning model with multi-source domains for biomedical event trigger extraction

Overview of attention for article published in BMC Genomics, January 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

twitter
1 X user
patent
1 patent

Readers on

mendeley
22 Mendeley
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Title
A transfer learning model with multi-source domains for biomedical event trigger extraction
Published in
BMC Genomics, January 2021
DOI 10.1186/s12864-020-07315-1
Pubmed ID
Authors

Yifei Chen

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 18%
Other 2 9%
Researcher 2 9%
Student > Ph. D. Student 2 9%
Professor 1 5%
Other 2 9%
Unknown 9 41%
Readers by discipline Count As %
Computer Science 7 32%
Nursing and Health Professions 1 5%
Earth and Planetary Sciences 1 5%
Medicine and Dentistry 1 5%
Neuroscience 1 5%
Other 1 5%
Unknown 10 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 28 September 2021.
All research outputs
#7,434,956
of 23,989,432 outputs
Outputs from BMC Genomics
#3,347
of 10,872 outputs
Outputs of similar age
#180,142
of 509,168 outputs
Outputs of similar age from BMC Genomics
#52
of 164 outputs
Altmetric has tracked 23,989,432 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 10,872 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 67% 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 509,168 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 164 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 67% of its contemporaries.