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Machine learning predictions of mean ages of shallow well samples in the Great Lakes Basin, USA

Overview of attention for article published in Journal of Hydrology, December 2021
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About this Attention Score

  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

twitter
3 X users

Citations

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11 Dimensions

Readers on

mendeley
31 Mendeley
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Title
Machine learning predictions of mean ages of shallow well samples in the Great Lakes Basin, USA
Published in
Journal of Hydrology, December 2021
DOI 10.1016/j.jhydrol.2021.126908
Authors

C.T. Green, K.M. Ransom, B.T. Nolan, L. Liao, T. Harter

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 13%
Student > Master 3 10%
Lecturer 2 6%
Unspecified 2 6%
Professor 2 6%
Other 4 13%
Unknown 14 45%
Readers by discipline Count As %
Environmental Science 4 13%
Unspecified 2 6%
Psychology 2 6%
Engineering 2 6%
Earth and Planetary Sciences 2 6%
Other 2 6%
Unknown 17 55%
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 18 September 2021.
All research outputs
#17,297,846
of 25,392,582 outputs
Outputs from Journal of Hydrology
#3,344
of 8,701 outputs
Outputs of similar age
#304,079
of 514,062 outputs
Outputs of similar age from Journal of Hydrology
#106
of 434 outputs
Altmetric has tracked 25,392,582 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 8,701 research outputs from this source. They receive a mean Attention Score of 3.2. This one has gotten more attention than average, scoring higher than 58% 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 514,062 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 434 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 74% of its contemporaries.