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Spatial scaling in multiscale models: methods for coupling agent-based and finite-element models of wound healing

Overview of attention for article published in Biomechanics and Modeling in Mechanobiology, April 2019
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1 X user

Citations

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Readers on

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31 Mendeley
Title
Spatial scaling in multiscale models: methods for coupling agent-based and finite-element models of wound healing
Published in
Biomechanics and Modeling in Mechanobiology, April 2019
DOI 10.1007/s10237-019-01145-1
Pubmed ID
Authors

Jia-Jye Lee, Lee Talman, Shayn M. Peirce, Jeffrey W. Holmes

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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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 32%
Professor 5 16%
Other 3 10%
Student > Master 3 10%
Lecturer 2 6%
Other 4 13%
Unknown 4 13%
Readers by discipline Count As %
Engineering 11 35%
Biochemistry, Genetics and Molecular Biology 2 6%
Environmental Science 1 3%
Agricultural and Biological Sciences 1 3%
Computer Science 1 3%
Other 6 19%
Unknown 9 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 08 February 2020.
All research outputs
#21,186,729
of 23,849,058 outputs
Outputs from Biomechanics and Modeling in Mechanobiology
#422
of 486 outputs
Outputs of similar age
#305,563
of 354,712 outputs
Outputs of similar age from Biomechanics and Modeling in Mechanobiology
#14
of 18 outputs
Altmetric has tracked 23,849,058 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 486 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 1st percentile – i.e., 1% 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 354,712 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.