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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Super machine learning: improving accuracy and reducing variance of behaviour classification from accelerometry
|
|---|---|
| Published in |
Animal Biotelemetry, March 2017
|
| DOI | 10.1186/s40317-017-0123-1 |
| Authors |
Monique A. Ladds, Adam P. Thompson, Julianna-Piroska Kadar, David J Slip, David P Hocking, Robert G Harcourt |
X Demographics
The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 6 | 35% |
| United Kingdom | 3 | 18% |
| Chile | 1 | 6% |
| United States | 1 | 6% |
| New Zealand | 1 | 6% |
| Unknown | 5 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 59% |
| Scientists | 7 | 41% |
Mendeley readers
The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 125 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 35 | 28% |
| Student > Master | 25 | 20% |
| Researcher | 15 | 12% |
| Student > Bachelor | 9 | 7% |
| Student > Doctoral Student | 5 | 4% |
| Other | 12 | 10% |
| Unknown | 24 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 53 | 42% |
| Environmental Science | 12 | 10% |
| Computer Science | 9 | 7% |
| Engineering | 6 | 5% |
| Business, Management and Accounting | 2 | 2% |
| Other | 9 | 7% |
| Unknown | 34 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 30 March 2018.
All research outputs
#3,235,724
of 24,549,201 outputs
Outputs from Animal Biotelemetry
#87
of 251 outputs
Outputs of similar age
#57,554
of 313,070 outputs
Outputs of similar age from Animal Biotelemetry
#4
of 7 outputs
Altmetric has tracked 24,549,201 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 251 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has gotten more attention than average, scoring higher than 65% 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 313,070 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 81% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.