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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Estimating Watershed Subsurface Permeability From Stream Discharge Data Using Deep Neural Networks
|
|---|---|
| Published in |
Frontiers in Earth Science, February 2021
|
| DOI | 10.3389/feart.2021.613011 |
| Authors |
Erol Cromwell, Pin Shuai, Peishi Jiang, Ethan T. Coon, Scott L. Painter, J. David Moulton, Youzuo Lin, Xingyuan Chen |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 40% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 18% |
| Student > Ph. D. Student | 5 | 15% |
| Other | 4 | 12% |
| Student > Postgraduate | 2 | 6% |
| Student > Master | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 12 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 7 | 21% |
| Earth and Planetary Sciences | 6 | 18% |
| Engineering | 5 | 15% |
| Psychology | 2 | 6% |
| Unspecified | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 13 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 27 September 2022.
All research outputs
#2,640,671
of 23,419,482 outputs
Outputs from Frontiers in Earth Science
#356
of 4,976 outputs
Outputs of similar age
#75,197
of 509,729 outputs
Outputs of similar age from Frontiers in Earth Science
#30
of 271 outputs
Altmetric has tracked 23,419,482 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,976 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 92% 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 509,729 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 271 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.