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A method for generating a quasi-linear convective system suitable for observing system simulation experiments

Overview of attention for article published in Geoscientific Model Development, March 2023
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
11 X users

Citations

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1 Dimensions

Readers on

mendeley
1 Mendeley
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Title
A method for generating a quasi-linear convective system suitable for observing system simulation experiments
Published in
Geoscientific Model Development, March 2023
DOI 10.5194/gmd-16-1779-2023
Authors

Jonathan D. Labriola, Jeremy A. Gibbs, Louis J. Wicker

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 100%
Readers by discipline Count As %
Earth and Planetary Sciences 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 30 March 2023.
All research outputs
#4,605,881
of 25,552,933 outputs
Outputs from Geoscientific Model Development
#294
of 2,074 outputs
Outputs of similar age
#87,049
of 422,979 outputs
Outputs of similar age from Geoscientific Model Development
#9
of 77 outputs
Altmetric has tracked 25,552,933 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,074 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 85% 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 422,979 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 77 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.