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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep learning approaches for improving prediction of daily stream temperature in data‐scarce, unmonitored, and dammed basins
|
|---|---|
| Published in |
Hydrological Processes, November 2021
|
| DOI | 10.1002/hyp.14400 |
| Authors |
Farshid Rahmani, Chaopeng Shen, Samantha Oliver, Kathryn Lawson, Alison Appling |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 63% |
| Morocco | 1 | 13% |
| Unknown | 2 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 75% |
| Scientists | 2 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 18% |
| Student > Doctoral Student | 4 | 14% |
| Researcher | 4 | 14% |
| Student > Ph. D. Student | 3 | 11% |
| Lecturer | 1 | 4% |
| Other | 4 | 14% |
| Unknown | 7 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 8 | 29% |
| Environmental Science | 4 | 14% |
| Computer Science | 3 | 11% |
| Arts and Humanities | 2 | 7% |
| Agricultural and Biological Sciences | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 7 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 05 August 2022.
All research outputs
#6,238,481
of 24,983,099 outputs
Outputs from Hydrological Processes
#502
of 2,058 outputs
Outputs of similar age
#129,628
of 516,005 outputs
Outputs of similar age from Hydrological Processes
#9
of 28 outputs
Altmetric has tracked 24,983,099 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 2,058 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 75% 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 516,005 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 74% of its contemporaries.
We're also able to compare this research output to 28 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 67% of its contemporaries.