| Title |
Mapping the space of chemical reactions using attention-based neural networks
|
|---|---|
| Published in |
Nature Machine Intelligence, January 2021
|
| DOI | 10.1038/s42256-020-00284-w |
| Authors |
Philippe Schwaller, Daniel Probst, Alain C. Vaucher, Vishnu H. Nair, David Kreutter, Teodoro Laino, Jean-Louis Reymond |
X Demographics
The data shown below were collected from the profiles of 139 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 | 26 | 19% |
| Switzerland | 20 | 14% |
| United Kingdom | 10 | 7% |
| Germany | 7 | 5% |
| Japan | 5 | 4% |
| Canada | 4 | 3% |
| France | 4 | 3% |
| India | 3 | 2% |
| Italy | 2 | 1% |
| Other | 11 | 8% |
| Unknown | 47 | 34% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 70 | 50% |
| Scientists | 63 | 45% |
| Science communicators (journalists, bloggers, editors) | 4 | 3% |
| Practitioners (doctors, other healthcare professionals) | 1 | <1% |
| Unknown | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 309 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 309 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 52 | 17% |
| Student > Ph. D. Student | 42 | 14% |
| Student > Bachelor | 33 | 11% |
| Student > Master | 23 | 7% |
| Other | 9 | 3% |
| Other | 22 | 7% |
| Unknown | 128 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 67 | 22% |
| Computer Science | 24 | 8% |
| Chemical Engineering | 17 | 6% |
| Engineering | 12 | 4% |
| Biochemistry, Genetics and Molecular Biology | 10 | 3% |
| Other | 40 | 13% |
| Unknown | 139 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 115. 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 30 November 2023.
All research outputs
#368,484
of 25,622,179 outputs
Outputs from Nature Machine Intelligence
#99
of 767 outputs
Outputs of similar age
#10,928
of 532,254 outputs
Outputs of similar age from Nature Machine Intelligence
#6
of 35 outputs
Altmetric has tracked 25,622,179 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 767 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 68.1. This one has done well, scoring higher than 87% 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 532,254 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 97% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.