| Title |
An operational machine learning approach to predict mosquito abundance based on socioeconomic and landscape patterns
|
|---|---|
| Published in |
Landscape Ecology, May 2019
|
| DOI | 10.1007/s10980-019-00839-2 |
| Authors |
Shi Chen, Ari Whiteman, Ang Li, Tyler Rapp, Eric Delmelle, Gang Chen, Cheryl L. Brown, Patrick Robinson, Maren J. Coffman, Daniel Janies, Michael Dulin |
X Demographics
The data shown below were collected from the profiles of 11 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 | 3 | 27% |
| Netherlands | 1 | 9% |
| India | 1 | 9% |
| Switzerland | 1 | 9% |
| Australia | 1 | 9% |
| United Kingdom | 1 | 9% |
| Unknown | 3 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 73% |
| Science communicators (journalists, bloggers, editors) | 2 | 18% |
| Scientists | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 79 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 20% |
| Student > Master | 9 | 11% |
| Student > Doctoral Student | 8 | 10% |
| Student > Ph. D. Student | 6 | 8% |
| Professor > Associate Professor | 5 | 6% |
| Other | 10 | 13% |
| Unknown | 25 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 16% |
| Environmental Science | 7 | 9% |
| Sports and Recreations | 5 | 6% |
| Nursing and Health Professions | 4 | 5% |
| Earth and Planetary Sciences | 4 | 5% |
| Other | 16 | 20% |
| Unknown | 30 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 12 June 2019.
All research outputs
#6,139,991
of 24,780,938 outputs
Outputs from Landscape Ecology
#566
of 1,671 outputs
Outputs of similar age
#102,923
of 355,992 outputs
Outputs of similar age from Landscape Ecology
#17
of 34 outputs
Altmetric has tracked 24,780,938 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,671 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has gotten more attention than average, scoring higher than 66% 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 355,992 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 70% of its contemporaries.
We're also able to compare this research output to 34 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 52% of its contemporaries.