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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2
|
|---|---|
| Published in |
Ecology and Evolution, September 2020
|
| DOI | 10.1002/ece3.6692 |
| Pubmed ID | |
| Authors |
Michael A. Tabak, Mohammad S. Norouzzadeh, David W. Wolfson, Erica J. Newton, Raoul K. Boughton, Jacob S. Ivan, Eric A. Odell, Eric S. Newkirk, Reesa Y. Conrey, Jennifer Stenglein, Fabiola Iannarilli, John Erb, Ryan K. Brook, Amy J. Davis, Jesse Lewis, Daniel P. Walsh, James C. Beasley, Kurt C. VerCauteren, Jeff Clune, Ryan S. Miller |
X Demographics
The data shown below were collected from the profiles of 64 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 | 14 | 22% |
| South Africa | 3 | 5% |
| United Kingdom | 2 | 3% |
| Canada | 2 | 3% |
| France | 2 | 3% |
| Croatia | 1 | 2% |
| New Zealand | 1 | 2% |
| Malaysia | 1 | 2% |
| Spain | 1 | 2% |
| Other | 5 | 8% |
| Unknown | 32 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 33 | 52% |
| Members of the public | 28 | 44% |
| Science communicators (journalists, bloggers, editors) | 2 | 3% |
| Unknown | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 112 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 19% |
| Student > Master | 18 | 16% |
| Student > Ph. D. Student | 16 | 14% |
| Student > Bachelor | 10 | 9% |
| Student > Doctoral Student | 5 | 4% |
| Other | 8 | 7% |
| Unknown | 34 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 29% |
| Environmental Science | 19 | 17% |
| Computer Science | 6 | 5% |
| Engineering | 3 | 3% |
| Veterinary Science and Veterinary Medicine | 2 | 2% |
| Other | 10 | 9% |
| Unknown | 40 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 60. 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 11 September 2023.
All research outputs
#707,271
of 25,387,668 outputs
Outputs from Ecology and Evolution
#294
of 8,480 outputs
Outputs of similar age
#20,245
of 414,888 outputs
Outputs of similar age from Ecology and Evolution
#13
of 280 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,480 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.0. This one has done particularly well, scoring higher than 96% 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 414,888 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 280 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.