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Passive acoustic monitoring and convolutional neural networks facilitate high-resolution and broadscale monitoring of a threatened species

Overview of attention for article published in Ecological Indicators, May 2024
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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 (#28 of 3,642)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
12 news outlets
twitter
8 X users
facebook
1 Facebook page
wikipedia
1 Wikipedia page

Readers on

mendeley
19 Mendeley
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Title
Passive acoustic monitoring and convolutional neural networks facilitate high-resolution and broadscale monitoring of a threatened species
Published in
Ecological Indicators, May 2024
DOI 10.1016/j.ecolind.2024.112016
Authors

Adam Duarte, Matthew J. Weldy, Damon B. Lesmeister, Zachary J. Ruff, Julianna M.A. Jenkins, Jonathon J. Valente, Matthew G. Betts

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Other 3 16%
Student > Ph. D. Student 3 16%
Researcher 3 16%
Student > Master 3 16%
Student > Doctoral Student 2 11%
Other 1 5%
Unknown 4 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 47%
Environmental Science 4 21%
Biochemistry, Genetics and Molecular Biology 2 11%
Unknown 4 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 96. 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 15 May 2024.
All research outputs
#454,526
of 25,911,277 outputs
Outputs from Ecological Indicators
#28
of 3,642 outputs
Outputs of similar age
#3,813
of 196,852 outputs
Outputs of similar age from Ecological Indicators
#1
of 20 outputs
Altmetric has tracked 25,911,277 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 3,642 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has done particularly well, scoring higher than 99% 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 196,852 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 20 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 95% of its contemporaries.