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X Demographics
Mendeley readers
Attention Score in Context
| Title |
From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2
|
|---|---|
| Published in |
Applications in Plant Sciences, October 2023
|
| DOI | 10.1002/aps3.11548 |
| Pubmed ID | |
| Authors |
William N. Weaver, Stephen A. Smith |
X Demographics
The data shown below were collected from the profiles of 71 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 | 20% |
| Colombia | 5 | 7% |
| United Kingdom | 5 | 7% |
| Canada | 3 | 4% |
| Spain | 2 | 3% |
| Italy | 1 | 1% |
| Finland | 1 | 1% |
| Ecuador | 1 | 1% |
| Dominican Republic | 1 | 1% |
| Other | 5 | 7% |
| Unknown | 33 | 46% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 38 | 54% |
| Scientists | 33 | 46% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 27% |
| Student > Ph. D. Student | 1 | 9% |
| Professor > Associate Professor | 1 | 9% |
| Student > Doctoral Student | 1 | 9% |
| Unknown | 5 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 36% |
| Computer Science | 1 | 9% |
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Unknown | 5 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 44. 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 20 November 2023.
All research outputs
#963,895
of 25,756,911 outputs
Outputs from Applications in Plant Sciences
#61
of 597 outputs
Outputs of similar age
#16,841
of 362,443 outputs
Outputs of similar age from Applications in Plant Sciences
#1
of 15 outputs
Altmetric has tracked 25,756,911 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 597 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one has done well, scoring higher than 89% 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 362,443 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 15 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 93% of its contemporaries.