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Object based Bayesian full-waveform inversion for shear elastography

Overview of attention for article published in Inverse Problems, June 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
9 X users

Readers on

mendeley
2 Mendeley
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Title
Object based Bayesian full-waveform inversion for shear elastography
Published in
Inverse Problems, June 2023
DOI 10.1088/1361-6420/acd5f8
Authors

Ana Carpio, Elena Cebrián, Andrea Gutiérrez

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 50%
Student > Ph. D. Student 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Materials Science 1 50%
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 13 May 2023.
All research outputs
#8,274,579
of 24,764,450 outputs
Outputs from Inverse Problems
#91
of 905 outputs
Outputs of similar age
#131,666
of 366,126 outputs
Outputs of similar age from Inverse Problems
#3
of 13 outputs
Altmetric has tracked 24,764,450 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 905 research outputs from this source. They receive a mean Attention Score of 1.8. This one has gotten more attention than average, scoring higher than 73% 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 366,126 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 62% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.