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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Monitoring canid scent marking in space and time using a biologging and machine learning approach
|
|---|---|
| Published in |
Scientific Reports, January 2020
|
| DOI | 10.1038/s41598-019-57198-w |
| Pubmed ID | |
| Authors |
Owen R. Bidder, Agustina di Virgilio, Jennifer S. Hunter, Alex McInturff, Kaitlyn M. Gaynor, Alison M. Smith, Janelle Dorcy, Frank Rosell |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 40% |
| France | 1 | 20% |
| Argentina | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 81 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 15% |
| Student > Ph. D. Student | 11 | 14% |
| Student > Master | 8 | 10% |
| Student > Bachelor | 8 | 10% |
| Unspecified | 4 | 5% |
| Other | 9 | 11% |
| Unknown | 29 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 23 | 28% |
| Environmental Science | 7 | 9% |
| Computer Science | 5 | 6% |
| Unspecified | 4 | 5% |
| Veterinary Science and Veterinary Medicine | 3 | 4% |
| Other | 8 | 10% |
| Unknown | 31 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 January 2020.
All research outputs
#6,841,122
of 23,189,371 outputs
Outputs from Scientific Reports
#45,784
of 125,386 outputs
Outputs of similar age
#145,544
of 455,853 outputs
Outputs of similar age from Scientific Reports
#1,617
of 4,297 outputs
Altmetric has tracked 23,189,371 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 125,386 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.3. This one has gotten more attention than average, scoring higher than 63% 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 455,853 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 67% of its contemporaries.
We're also able to compare this research output to 4,297 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 62% of its contemporaries.