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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep learning accurately predicts white shark locomotor activity from depth data
|
|---|---|
| Published in |
Animal Biotelemetry, August 2019
|
| DOI | 10.1186/s40317-019-0175-5 |
| Authors |
Zac Yung-Chun Liu, Jerry H. Moxley, Paul Kanive, Adrian C. Gleiss, Thom Maughan, Larry Bird, Oliver J. D. Jewell, Taylor K. Chapple, Tyler Gagne, Connor F. White, Salvador J. Jorgensen |
X Demographics
The data shown below were collected from the profiles of 12 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 | 4 | 33% |
| Australia | 3 | 25% |
| Switzerland | 1 | 8% |
| United Kingdom | 1 | 8% |
| Unknown | 3 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 58% |
| Members of the public | 5 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 57 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 13 | 23% |
| Researcher | 12 | 21% |
| Student > Ph. D. Student | 8 | 14% |
| Student > Bachelor | 7 | 12% |
| Student > Doctoral Student | 3 | 5% |
| Other | 8 | 14% |
| Unknown | 6 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 23 | 40% |
| Environmental Science | 7 | 12% |
| Computer Science | 6 | 11% |
| Engineering | 3 | 5% |
| Social Sciences | 2 | 4% |
| Other | 5 | 9% |
| Unknown | 11 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 10 September 2019.
All research outputs
#4,167,407
of 23,458,084 outputs
Outputs from Animal Biotelemetry
#107
of 239 outputs
Outputs of similar age
#80,660
of 342,497 outputs
Outputs of similar age from Animal Biotelemetry
#5
of 6 outputs
Altmetric has tracked 23,458,084 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 239 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one has gotten more attention than average, scoring higher than 54% 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 342,497 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 76% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.