↓ Skip to main content

Potential of deep predictive coding networks for spatiotemporal tsunami wavefield prediction

Overview of attention for article published in Geoscience Letters, November 2020
Altmetric Badge

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 (57th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
10 Mendeley
Title
Potential of deep predictive coding networks for spatiotemporal tsunami wavefield prediction
Published in
Geoscience Letters, November 2020
DOI 10.1186/s40562-020-00169-1
Authors

Ardiansyah Fauzi, Norimi Mizutani

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 20%
Lecturer 1 10%
Other 1 10%
Researcher 1 10%
Professor > Associate Professor 1 10%
Other 0 0%
Unknown 4 40%
Readers by discipline Count As %
Engineering 3 30%
Earth and Planetary Sciences 2 20%
Unknown 5 50%
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 21 November 2020.
All research outputs
#14,525,076
of 23,263,851 outputs
Outputs from Geoscience Letters
#77
of 194 outputs
Outputs of similar age
#270,721
of 508,016 outputs
Outputs of similar age from Geoscience Letters
#3
of 7 outputs
Altmetric has tracked 23,263,851 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 194 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 55% 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 508,016 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.