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Computationally-Optimized Bone Mechanical Modeling from High-Resolution Structural Images

Overview of attention for article published in PLOS ONE, April 2012
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
54 Mendeley
citeulike
1 CiteULike
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Title
Computationally-Optimized Bone Mechanical Modeling from High-Resolution Structural Images
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0035525
Pubmed ID
Authors

Jeremy F. Magland, Ning Zhang, Chamith S. Rajapakse, Felix W. Wehrli

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Unknown 53 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 19%
Researcher 9 17%
Student > Master 8 15%
Student > Doctoral Student 4 7%
Professor 4 7%
Other 12 22%
Unknown 7 13%
Readers by discipline Count As %
Engineering 22 41%
Medicine and Dentistry 10 19%
Mathematics 3 6%
Sports and Recreations 3 6%
Nursing and Health Professions 1 2%
Other 4 7%
Unknown 11 20%
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 06 December 2018.
All research outputs
#7,610,424
of 23,204,238 outputs
Outputs from PLOS ONE
#92,086
of 198,307 outputs
Outputs of similar age
#54,610
of 164,377 outputs
Outputs of similar age from PLOS ONE
#1,491
of 3,749 outputs
Altmetric has tracked 23,204,238 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 198,307 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.2. This one is in the 49th percentile – i.e., 49% 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 164,377 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,749 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 52% of its contemporaries.