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Machine learning for efficient segregation and labeling of potential biological sounds in long-term underwater recordings

Overview of attention for article published in Frontiers in Remote Sensing, April 2024
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2 X users

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3 Mendeley
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Title
Machine learning for efficient segregation and labeling of potential biological sounds in long-term underwater recordings
Published in
Frontiers in Remote Sensing, April 2024
DOI 10.3389/frsen.2024.1390687
Authors

Clea Parcerisas, Elena Schall, Kees te Velde, Dick Botteldooren, Paul Devos, Elisabeth Debusschere

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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 33%
Researcher 1 33%
Student > Doctoral Student 1 33%
Readers by discipline Count As %
Environmental Science 1 33%
Agricultural and Biological Sciences 1 33%
Earth and Planetary Sciences 1 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 25 April 2024.
All research outputs
#17,732,227
of 25,992,468 outputs
Outputs from Frontiers in Remote Sensing
#1
of 1 outputs
Outputs of similar age
#135,307
of 264,774 outputs
Outputs of similar age from Frontiers in Remote Sensing
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 1.0. This one scored the same or higher as 0 of them.
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 264,774 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them