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Serial KinderMiner (SKiM) discovers and annotates biomedical knowledge using co-occurrence and transformer models

Overview of attention for article published in BMC Bioinformatics, November 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Serial KinderMiner (SKiM) discovers and annotates biomedical knowledge using co-occurrence and transformer models
Published in
BMC Bioinformatics, November 2023
DOI 10.1186/s12859-023-05539-y
Pubmed ID
Authors

Robert J. Millikin, Kalpana Raja, John Steill, Cannon Lock, Xuancheng Tu, Ian Ross, Lam C. Tsoi, Finn Kuusisto, Zijian Ni, Miron Livny, Brian Bockelman, James Thomson, Ron Stewart

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 14%
Researcher 1 14%
Unknown 5 71%
Readers by discipline Count As %
Unspecified 1 14%
Computer Science 1 14%
Unknown 5 71%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 20 December 2023.
All research outputs
#14,563,896
of 25,028,065 outputs
Outputs from BMC Bioinformatics
#4,182
of 7,637 outputs
Outputs of similar age
#126,432
of 332,001 outputs
Outputs of similar age from BMC Bioinformatics
#28
of 87 outputs
Altmetric has tracked 25,028,065 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,637 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 44th percentile – i.e., 44% 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 332,001 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 61% of its contemporaries.
We're also able to compare this research output to 87 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 68% of its contemporaries.