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Attention Score in Context
Deep learning approach for detecting tropical cyclones and their precursors in the simulation by a cloud-resolving global nonhydrostatic atmospheric model
Progress in Earth and Planetary Science, December 2018
Daisuke Matsuoka, Masuo Nakano, Daisuke Sugiyama, Seiichi Uchida
The data shown below were collected from the profiles of 37 X users who shared this research output. Click here to find out more about how the information was compiled.
|Members of the public||32||86%|
|Science communicators (journalists, bloggers, editors)||1||3%|
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
|Readers by professional status||Count||As %|
|Student > Ph. D. Student||13||16%|
|Student > Master||9||11%|
|Student > Doctoral Student||3||4%|
|Readers by discipline||Count||As %|
|Earth and Planetary Sciences||19||24%|
|Agricultural and Biological Sciences||2||3%|
Attention Score in Context
This research output has an Altmetric Attention Score of 25. 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 07 September 2021.
All research outputs
of 24,226,848 outputs
Outputs from Progress in Earth and Planetary Science
of 556 outputs
Outputs of similar age
of 443,867 outputs
Outputs of similar age from Progress in Earth and Planetary Science
of 29 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 556 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one has done particularly well, scoring higher than 96% 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 443,867 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 29 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.