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A Statistical Method to Predict Flow Permanence in Dryland Streams from Time Series of Stream Temperature

Overview of attention for article published in Water (20734441), December 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
30 Mendeley
Title
A Statistical Method to Predict Flow Permanence in Dryland Streams from Time Series of Stream Temperature
Published in
Water (20734441), December 2017
DOI 10.3390/w9120946
Authors

Ivan Arismendi, Jason Dunham, Michael Heck, Luke Schultz, David Hockman-Wert

Twitter Demographics

The data shown below were collected from the profiles of 5 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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 27%
Student > Master 6 20%
Student > Ph. D. Student 5 17%
Student > Postgraduate 2 7%
Professor 2 7%
Other 4 13%
Unknown 3 10%
Readers by discipline Count As %
Environmental Science 13 43%
Agricultural and Biological Sciences 6 20%
Earth and Planetary Sciences 4 13%
Biochemistry, Genetics and Molecular Biology 1 3%
Engineering 1 3%
Other 0 0%
Unknown 5 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 22 July 2020.
All research outputs
#4,561,337
of 15,550,579 outputs
Outputs from Water (20734441)
#605
of 3,110 outputs
Outputs of similar age
#134,474
of 408,416 outputs
Outputs of similar age from Water (20734441)
#19
of 120 outputs
Altmetric has tracked 15,550,579 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 3,110 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 79% 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 408,416 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.