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X Demographics
Mendeley readers
Attention Score in Context
Title |
Dataset’s chemical diversity limits the generalizability of machine learning predictions
|
---|---|
Published in |
Journal of Cheminformatics, November 2019
|
DOI | 10.1186/s13321-019-0391-2 |
Pubmed ID | |
Authors |
Marta Glavatskikh, Jules Leguy, Gilles Hunault, Thomas Cauchy, Benoit Da Mota |
X Demographics
The data shown below were collected from the profiles of 19 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 | 2 | 11% |
France | 1 | 5% |
Korea, Republic of | 1 | 5% |
Thailand | 1 | 5% |
Canada | 1 | 5% |
United Arab Emirates | 1 | 5% |
Norway | 1 | 5% |
India | 1 | 5% |
Sweden | 1 | 5% |
Other | 0 | 0% |
Unknown | 9 | 47% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 12 | 63% |
Members of the public | 6 | 32% |
Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 107 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 27 | 25% |
Researcher | 16 | 15% |
Student > Master | 13 | 12% |
Student > Bachelor | 8 | 7% |
Student > Doctoral Student | 5 | 5% |
Other | 10 | 9% |
Unknown | 28 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 30 | 28% |
Engineering | 9 | 8% |
Computer Science | 7 | 7% |
Chemical Engineering | 7 | 7% |
Physics and Astronomy | 5 | 5% |
Other | 18 | 17% |
Unknown | 31 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 03 June 2021.
All research outputs
#3,087,836
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#304
of 891 outputs
Outputs of similar age
#63,428
of 363,851 outputs
Outputs of similar age from Journal of Cheminformatics
#6
of 18 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. Compared to these this one has done well and is in the 87th 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 10.7. This one has gotten more attention than average, scoring higher than 65% 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 363,851 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 82% of its contemporaries.
We're also able to compare this research output to 18 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 72% of its contemporaries.