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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A need for speed in Bayesian population models: a practical guide to marginalizing and recovering discrete latent states
|
|---|---|
| Published in |
Ecological Applications, April 2020
|
| DOI | 10.1002/eap.2112 |
| Pubmed ID | |
| Authors |
Charles B. Yackulic, Michael Dodrill, Maria Dzul, Jamie S. Sanderlin, Janice A. Reid |
X Demographics
The data shown below were collected from the profiles of 47 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 | 12 | 26% |
| France | 3 | 6% |
| Australia | 3 | 6% |
| United Kingdom | 2 | 4% |
| Canada | 2 | 4% |
| Argentina | 2 | 4% |
| Spain | 1 | 2% |
| Costa Rica | 1 | 2% |
| Netherlands | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 19 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 27 | 57% |
| Scientists | 20 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 85 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 27% |
| Researcher | 23 | 27% |
| Student > Master | 8 | 9% |
| Student > Bachelor | 7 | 8% |
| Student > Doctoral Student | 5 | 6% |
| Other | 10 | 12% |
| Unknown | 9 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 41 | 48% |
| Environmental Science | 15 | 18% |
| Social Sciences | 5 | 6% |
| Engineering | 2 | 2% |
| Business, Management and Accounting | 1 | 1% |
| Other | 5 | 6% |
| Unknown | 16 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 27. 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 29 April 2022.
All research outputs
#1,464,685
of 25,726,194 outputs
Outputs from Ecological Applications
#401
of 3,350 outputs
Outputs of similar age
#37,995
of 397,898 outputs
Outputs of similar age from Ecological Applications
#10
of 61 outputs
Altmetric has tracked 25,726,194 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,350 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.6. This one has done well, scoring higher than 88% 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 397,898 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 90% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.