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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using Convolutional Neural Networks to Efficiently Extract Immense Phenological Data From Community Science Images
|
|---|---|
| Published in |
Frontiers in Plant Science, January 2022
|
| DOI | 10.3389/fpls.2021.787407 |
| Pubmed ID | |
| Authors |
Rachel A. Reeb, Naeem Aziz, Samuel M. Lapp, Justin Kitzes, J. Mason Heberling, Sara E. Kuebbing |
X Demographics
The data shown below were collected from the profiles of 18 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 | 7 | 39% |
| India | 1 | 6% |
| United Kingdom | 1 | 6% |
| Mexico | 1 | 6% |
| Switzerland | 1 | 6% |
| Unknown | 7 | 39% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 13 | 72% |
| Scientists | 5 | 28% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 25% |
| Student > Ph. D. Student | 4 | 14% |
| Student > Bachelor | 4 | 14% |
| Student > Postgraduate | 2 | 7% |
| Student > Doctoral Student | 2 | 7% |
| Other | 1 | 4% |
| Unknown | 8 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 29% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Earth and Planetary Sciences | 2 | 7% |
| Social Sciences | 2 | 7% |
| Immunology and Microbiology | 1 | 4% |
| Other | 3 | 11% |
| Unknown | 10 | 36% |
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 26 January 2022.
All research outputs
#3,375,272
of 25,401,381 outputs
Outputs from Frontiers in Plant Science
#1,682
of 24,635 outputs
Outputs of similar age
#81,164
of 515,430 outputs
Outputs of similar age from Frontiers in Plant Science
#60
of 1,030 outputs
Altmetric has tracked 25,401,381 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 24,635 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 93% 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 515,430 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 84% of its contemporaries.
We're also able to compare this research output to 1,030 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 94% of its contemporaries.