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Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data

Overview of attention for article published in Environmental Research Letters (ERL), December 2020
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

twitter
42 tweeters

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
27 Mendeley
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Title
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data
Published in
Environmental Research Letters (ERL), December 2020
DOI 10.1088/1748-9326/abd501
Authors

Farshid Rahmani, Kathryn Lawson, Wenyu Ouyang, Alison Appling, Samantha Oliver, Chaopeng Shen

Twitter Demographics

The data shown below were collected from the profiles of 42 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 37%
Student > Master 5 19%
Researcher 4 15%
Student > Doctoral Student 2 7%
Professor > Associate Professor 2 7%
Other 0 0%
Unknown 4 15%
Readers by discipline Count As %
Environmental Science 8 30%
Agricultural and Biological Sciences 4 15%
Engineering 4 15%
Earth and Planetary Sciences 2 7%
Unknown 9 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 16 January 2021.
All research outputs
#922,029
of 18,846,859 outputs
Outputs from Environmental Research Letters (ERL)
#1,190
of 4,571 outputs
Outputs of similar age
#33,508
of 435,043 outputs
Outputs of similar age from Environmental Research Letters (ERL)
#30
of 84 outputs
Altmetric has tracked 18,846,859 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,571 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.0. This one has gotten more attention than average, scoring higher than 73% 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 435,043 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 92% of its contemporaries.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.