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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Molecular optimization by capturing chemist’s intuition using deep neural networks
|
|---|---|
| Published in |
Journal of Cheminformatics, March 2021
|
| DOI | 10.1186/s13321-021-00497-0 |
| Pubmed ID | |
| Authors |
Jiazhen He, Huifang You, Emil Sandström, Eva Nittinger, Esben Jannik Bjerrum, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist |
X Demographics
The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 4 | 15% |
| Sweden | 3 | 11% |
| United States | 2 | 7% |
| France | 2 | 7% |
| Chile | 1 | 4% |
| Switzerland | 1 | 4% |
| Venezuela, Bolivarian Republic of | 1 | 4% |
| United Kingdom | 1 | 4% |
| Unknown | 12 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 19 | 70% |
| Scientists | 7 | 26% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 120 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 26% |
| Student > Ph. D. Student | 18 | 15% |
| Student > Master | 14 | 12% |
| Other | 5 | 4% |
| Student > Bachelor | 3 | 3% |
| Other | 8 | 7% |
| Unknown | 41 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 26 | 22% |
| Computer Science | 11 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 5% |
| Agricultural and Biological Sciences | 6 | 5% |
| Engineering | 6 | 5% |
| Other | 20 | 17% |
| Unknown | 45 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 21. 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 03 November 2023.
All research outputs
#1,743,159
of 24,998,746 outputs
Outputs from Journal of Cheminformatics
#129
of 938 outputs
Outputs of similar age
#45,393
of 430,796 outputs
Outputs of similar age from Journal of Cheminformatics
#4
of 31 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 938 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has done well, scoring higher than 86% 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 430,796 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 31 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 90% of its contemporaries.