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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Multi-channel PINN: investigating scalable and transferable neural networks for drug discovery
|
|---|---|
| Published in |
Journal of Cheminformatics, July 2019
|
| DOI | 10.1186/s13321-019-0368-1 |
| Pubmed ID | |
| Authors |
Munhwan Lee, Hyeyeon Kim, Hyunwhan Joe, Hong-Gee Kim |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Scientists | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 25% |
| Student > Master | 9 | 19% |
| Researcher | 8 | 17% |
| Student > Bachelor | 3 | 6% |
| Student > Doctoral Student | 3 | 6% |
| Other | 6 | 13% |
| Unknown | 7 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 11 | 23% |
| Engineering | 6 | 13% |
| Chemistry | 6 | 13% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Agricultural and Biological Sciences | 3 | 6% |
| Other | 9 | 19% |
| Unknown | 10 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 31 July 2019.
All research outputs
#15,867,545
of 23,577,761 outputs
Outputs from Journal of Cheminformatics
#791
of 874 outputs
Outputs of similar age
#214,842
of 347,758 outputs
Outputs of similar age from Journal of Cheminformatics
#20
of 21 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 874 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 4th percentile – i.e., 4% of its peers scored the same or lower than it.
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 347,758 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.