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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Translating the InChI: adapting neural machine translation to predict IUPAC names from a chemical identifier
|
|---|---|
| Published in |
Journal of Cheminformatics, October 2021
|
| DOI | 10.1186/s13321-021-00535-x |
| Pubmed ID | |
| Authors |
Jennifer Handsel, Brian Matthews, Nicola J. Knight, Simon J. Coles |
X Demographics
The data shown below were collected from the profiles of 10 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 Kingdom | 2 | 20% |
| Sweden | 2 | 20% |
| Switzerland | 1 | 10% |
| United States | 1 | 10% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 60% |
| Scientists | 3 | 30% |
| Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 14% |
| Lecturer | 2 | 9% |
| Student > Doctoral Student | 2 | 9% |
| Student > Bachelor | 2 | 9% |
| Student > Ph. D. Student | 2 | 9% |
| Other | 4 | 18% |
| Unknown | 7 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 4 | 18% |
| Chemical Engineering | 2 | 9% |
| Biochemistry, Genetics and Molecular Biology | 2 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Arts and Humanities | 1 | 5% |
| Other | 4 | 18% |
| Unknown | 8 | 36% |
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 09 October 2021.
All research outputs
#5,051,040
of 24,224,854 outputs
Outputs from Journal of Cheminformatics
#443
of 891 outputs
Outputs of similar age
#108,125
of 424,340 outputs
Outputs of similar age from Journal of Cheminformatics
#12
of 27 outputs
Altmetric has tracked 24,224,854 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 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 50% 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 424,340 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 27 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 59% of its contemporaries.