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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Automatic acoustic recognition of pollinating bee species can be highly improved by Deep Learning models accompanied by pre-training and strong data augmentation
|
|---|---|
| Published in |
Frontiers in Plant Science, April 2023
|
| DOI | 10.3389/fpls.2023.1081050 |
| Pubmed ID | |
| Authors |
Alef Iury Siqueira Ferreira, Nádia Felix Felipe da Silva, Fernanda Neiva Mesquita, Thierson Couto Rosa, Victor Hugo Monzón, José Neiva Mesquita-Neto |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 25% |
| Chile | 1 | 25% |
| Switzerland | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Postgraduate | 2 | 10% |
| Researcher | 2 | 10% |
| Other | 1 | 5% |
| Lecturer | 1 | 5% |
| Student > Bachelor | 1 | 5% |
| Other | 3 | 15% |
| Unknown | 10 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 20% |
| Computer Science | 4 | 20% |
| Environmental Science | 2 | 10% |
| Unknown | 10 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 19 April 2023.
All research outputs
#13,807,674
of 23,578,918 outputs
Outputs from Frontiers in Plant Science
#6,767
of 21,663 outputs
Outputs of similar age
#102,064
of 253,783 outputs
Outputs of similar age from Frontiers in Plant Science
#123
of 681 outputs
Altmetric has tracked 23,578,918 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 21,663 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 68% 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 253,783 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 59% of its contemporaries.
We're also able to compare this research output to 681 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.