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Leveraging Deep Learning in Global 24/7 Real-Time Earthquake Monitoring at the National Earthquake Information Center

Overview of attention for article published in Seismological Research Letters, September 2020
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  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
33 Mendeley
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Title
Leveraging Deep Learning in Global 24/7 Real-Time Earthquake Monitoring at the National Earthquake Information Center
Published in
Seismological Research Letters, September 2020
DOI 10.1785/0220200178
Authors

William Luther Yeck, John M. Patton, Zachary E. Ross, Gavin P. Hayes, Michelle R. Guy, Nick B. Ambruz, David R. Shelly, Harley M. Benz, Paul S. Earle

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 33%
Student > Ph. D. Student 8 24%
Student > Doctoral Student 3 9%
Student > Master 3 9%
Student > Bachelor 1 3%
Other 1 3%
Unknown 6 18%
Readers by discipline Count As %
Earth and Planetary Sciences 23 70%
Computer Science 1 3%
Economics, Econometrics and Finance 1 3%
Unknown 8 24%

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 23 September 2020.
All research outputs
#13,391,774
of 21,479,159 outputs
Outputs from Seismological Research Letters
#835
of 1,193 outputs
Outputs of similar age
#181,945
of 327,142 outputs
Outputs of similar age from Seismological Research Letters
#49
of 67 outputs
Altmetric has tracked 21,479,159 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 1,193 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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 327,142 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.