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X Demographics
Mendeley readers
Attention Score in Context
| Title |
From theory to experiment: transformer-based generation enables rapid discovery of novel reactions
|
|---|---|
| Published in |
Journal of Cheminformatics, September 2022
|
| DOI | 10.1186/s13321-022-00638-z |
| Pubmed ID | |
| Authors |
Xinqiao Wang, Chuansheng Yao, Yun Zhang, Jiahui Yu, Haoran Qiao, Chengyun Zhang, Yejian Wu, Renren Bai, Hongliang Duan |
X Demographics
The data shown below were collected from the profiles of 15 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 | 27% |
| Austria | 1 | 7% |
| France | 1 | 7% |
| Unknown | 9 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 67% |
| Scientists | 4 | 27% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 18% |
| Student > Ph. D. Student | 3 | 18% |
| Unspecified | 1 | 6% |
| Other | 1 | 6% |
| Student > Doctoral Student | 1 | 6% |
| Other | 2 | 12% |
| Unknown | 6 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 4 | 24% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Unspecified | 1 | 6% |
| Computer Science | 1 | 6% |
| Other | 3 | 18% |
| Unknown | 6 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 27 January 2023.
All research outputs
#5,069,426
of 24,903,209 outputs
Outputs from Journal of Cheminformatics
#440
of 934 outputs
Outputs of similar age
#101,690
of 423,274 outputs
Outputs of similar age from Journal of Cheminformatics
#9
of 22 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 934 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 52% 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 423,274 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 75% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.