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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Bitbow Enables Highly Efficient Neuronal Lineage Tracing and Morphology Reconstruction in Single Drosophila Brains
|
|---|---|
| Published in |
Frontiers in Neural Circuits, October 2021
|
| DOI | 10.3389/fncir.2021.732183 |
| Pubmed ID | |
| Authors |
Ye Li, Logan A. Walker, Yimeng Zhao, Erica M. Edwards, Nigel S. Michki, Pong Jimmy Cheng, Marya Ghazzi, Tiffany Y. Chen, Maggie Chen, Douglas H. Roossien, Dawen Cai |
X Demographics
The data shown below were collected from the profiles of 10 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 | 30% |
| Switzerland | 2 | 20% |
| Korea, Democratic People's Republic of | 1 | 10% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 90% |
| Scientists | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 21% |
| Researcher | 6 | 18% |
| Student > Bachelor | 4 | 12% |
| Student > Postgraduate | 2 | 6% |
| Student > Master | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 9 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 27% |
| Neuroscience | 7 | 21% |
| Biochemistry, Genetics and Molecular Biology | 5 | 15% |
| Business, Management and Accounting | 1 | 3% |
| Medicine and Dentistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 9 | 27% |
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 11 December 2021.
All research outputs
#6,362,786
of 25,827,956 outputs
Outputs from Frontiers in Neural Circuits
#328
of 1,303 outputs
Outputs of similar age
#117,571
of 444,279 outputs
Outputs of similar age from Frontiers in Neural Circuits
#8
of 47 outputs
Altmetric has tracked 25,827,956 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 1,303 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has gotten more attention than average, scoring higher than 74% 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 444,279 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 73% of its contemporaries.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.