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Development and analysis of a Bayesian water balance model for large lake systems

Overview of attention for article published in arXiv, October 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
6 tweeters

Readers on

mendeley
8 Mendeley
Title
Development and analysis of a Bayesian water balance model for large lake systems
Published in
arXiv, October 2017
Authors

Joeseph P. Smith, Andrew D. Gronewold

Twitter Demographics

The data shown below were collected from the profiles of 6 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 38%
Professor 1 13%
Unknown 4 50%
Readers by discipline Count As %
Engineering 3 38%
Earth and Planetary Sciences 1 13%
Unknown 4 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 23 January 2020.
All research outputs
#8,156,415
of 15,482,068 outputs
Outputs from arXiv
#122,994
of 602,271 outputs
Outputs of similar age
#132,936
of 322,013 outputs
Outputs of similar age from arXiv
#4,722
of 22,446 outputs
Altmetric has tracked 15,482,068 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 602,271 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 78% 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 322,013 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 57% of its contemporaries.
We're also able to compare this research output to 22,446 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.