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A machine learning approach to robustly determine director fields and analyze defects in active nematics

Overview of attention for article published in Soft Matter, January 2024
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
6 X users

Readers on

mendeley
7 Mendeley
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Article details
Title
A machine learning approach to robustly determine director fields and analyze defects in active nematics
Published in
Soft Matter, January 2024
DOI 10.1039/d3sm01253k
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

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

Geographical breakdown
Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Professor 1 14%
Researcher 1 14%
Student > Doctoral Student 1 14%
Student > Master 1 14%
Unknown 3 43%
Readers by discipline
Readers by discipline Count As %
Physics and Astronomy 3 43%
Social Sciences 1 14%
Unknown 3 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 09 February 2024.
All research outputs
#21,022,626
of 33,043,360 outputs
Outputs from Soft Matter
#4,000
of 10,050 outputs
Outputs of similar age
#201,481
of 433,699 outputs
Outputs of similar age from Soft Matter
#116
of 330 outputs
Altmetric has tracked 33,043,360 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,050 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 58% 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 433,699 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 51% of its contemporaries.
We're also able to compare this research output to 330 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 63% of its contemporaries.