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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of small-molecule compound solubility in organic solvents by machine learning algorithms
|
|---|---|
| Published in |
Journal of Cheminformatics, December 2021
|
| DOI | 10.1186/s13321-021-00575-3 |
| Pubmed ID | |
| Authors |
Zhuyifan Ye, Defang Ouyang |
X Demographics
The data shown below were collected from the profiles of 11 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 | 3 | 27% |
| India | 2 | 18% |
| Brazil | 1 | 9% |
| Unknown | 5 | 45% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 55% |
| Members of the public | 4 | 36% |
| Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 75 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 12% |
| Student > Master | 8 | 11% |
| Researcher | 5 | 7% |
| Student > Bachelor | 4 | 5% |
| Professor > Associate Professor | 3 | 4% |
| Other | 8 | 11% |
| Unknown | 38 | 51% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 12 | 16% |
| Chemical Engineering | 5 | 7% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Agricultural and Biological Sciences | 2 | 3% |
| Other | 8 | 11% |
| Unknown | 41 | 55% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 20 December 2021.
All research outputs
#6,057,994
of 24,254,113 outputs
Outputs from Journal of Cheminformatics
#473
of 893 outputs
Outputs of similar age
#128,220
of 508,962 outputs
Outputs of similar age from Journal of Cheminformatics
#9
of 20 outputs
Altmetric has tracked 24,254,113 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 893 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 47th percentile – i.e., 47% 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 508,962 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 74% of its contemporaries.
We're also able to compare this research output to 20 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 60% of its contemporaries.