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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine Learning-Boosted Docking Enables the Efficient Structure-Based Virtual Screening of Giga-Scale Enumerated Chemical Libraries
|
|---|---|
| Published in |
Journal of Chemical Information and Modeling, September 2023
|
| DOI | 10.1021/acs.jcim.3c01239 |
| Pubmed ID | |
| Authors |
Toni Sivula, Laxman Yetukuri, Tuomo Kalliokoski, Heikki Käsnänen, Antti Poso, Ina Pöhner |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 4% |
| Finland | 1 | 4% |
| Unknown | 22 | 92% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 50% |
| Scientists | 11 | 46% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 49 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 33% |
| Student > Ph. D. Student | 3 | 6% |
| Professor > Associate Professor | 2 | 4% |
| Student > Master | 2 | 4% |
| Unspecified | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 20 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 12 | 24% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 8% |
| Agricultural and Biological Sciences | 3 | 6% |
| Computer Science | 3 | 6% |
| Biochemistry, Genetics and Molecular Biology | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 21 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 164. 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 25 February 2024.
All research outputs
#254,423
of 25,859,234 outputs
Outputs from Journal of Chemical Information and Modeling
#8
of 5,831 outputs
Outputs of similar age
#4,807
of 358,784 outputs
Outputs of similar age from Journal of Chemical Information and Modeling
#2
of 186 outputs
Altmetric has tracked 25,859,234 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,831 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done particularly well, scoring higher than 99% 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 358,784 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 98% of its contemporaries.
We're also able to compare this research output to 186 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 98% of its contemporaries.