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MistNet: Measuring historical bird migration in the US using archived weather radar data and convolutional neural networks

Overview of attention for article published in Methods in Ecology and Evolution, August 2019
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#39 of 2,513)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
9 news outlets
blogs
3 blogs
twitter
102 X users
facebook
2 Facebook pages

Citations

dimensions_citation
55 Dimensions

Readers on

mendeley
105 Mendeley
Title
MistNet: Measuring historical bird migration in the US using archived weather radar data and convolutional neural networks
Published in
Methods in Ecology and Evolution, August 2019
DOI 10.1111/2041-210x.13280
Authors

Tsung‐Yu Lin, Kevin Winner, Garrett Bernstein, Abhay Mittal, Adriaan M. Dokter, Kyle G. Horton, Cecilia Nilsson, Benjamin M. Van Doren, Andrew Farnsworth, Frank A. La Sorte, Subhransu Maji, Daniel Sheldon

X Demographics

X Demographics

The data shown below were collected from the profiles of 102 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 105 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 23%
Researcher 16 15%
Student > Master 11 10%
Student > Bachelor 6 6%
Other 6 6%
Other 13 12%
Unknown 29 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 37%
Environmental Science 12 11%
Computer Science 12 11%
Engineering 4 4%
Mathematics 2 2%
Other 7 7%
Unknown 29 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 147. 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 28 February 2020.
All research outputs
#297,941
of 26,375,927 outputs
Outputs from Methods in Ecology and Evolution
#39
of 2,513 outputs
Outputs of similar age
#5,755
of 352,948 outputs
Outputs of similar age from Methods in Ecology and Evolution
#2
of 63 outputs
Altmetric has tracked 26,375,927 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.1. This one has done particularly well, scoring higher than 98% 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 352,948 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 98% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.