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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting chemical structure using reinforcement learning with a stack-augmented conditional variational autoencoder
|
|---|---|
| Published in |
Journal of Cheminformatics, December 2022
|
| DOI | 10.1186/s13321-022-00666-9 |
| Pubmed ID | |
| Authors |
Hwanhee Kim, Soohyun Ko, Byung Ju Kim, Sung Jin Ryu, Jaegyoon Ahn |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 5 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 2 | 17% |
| Student > Ph. D. Student | 2 | 17% |
| Researcher | 2 | 17% |
| Student > Doctoral Student | 1 | 8% |
| Student > Master | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 3 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemical Engineering | 2 | 17% |
| Unspecified | 1 | 8% |
| Environmental Science | 1 | 8% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Agricultural and Biological Sciences | 1 | 8% |
| Other | 3 | 25% |
| Unknown | 3 | 25% |
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 29 December 2022.
All research outputs
#14,973,293
of 25,076,138 outputs
Outputs from Journal of Cheminformatics
#725
of 943 outputs
Outputs of similar age
#203,780
of 482,553 outputs
Outputs of similar age from Journal of Cheminformatics
#20
of 27 outputs
Altmetric has tracked 25,076,138 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 943 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 20th percentile – i.e., 20% 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 482,553 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.