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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra
|
|---|---|
| Published in |
Journal of Cheminformatics, October 2021
|
| DOI | 10.1186/s13321-021-00558-4 |
| Pubmed ID | |
| Authors |
Florian Huber, Sven van der Burg, Justin J. J. van der Hooft, Lars Ridder |
X Demographics
The data shown below were collected from the profiles of 35 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 | 9% |
| Japan | 3 | 9% |
| Netherlands | 3 | 9% |
| United Kingdom | 1 | 3% |
| Germany | 1 | 3% |
| Denmark | 1 | 3% |
| Malaysia | 1 | 3% |
| France | 1 | 3% |
| Sweden | 1 | 3% |
| Other | 5 | 14% |
| Unknown | 15 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 21 | 60% |
| Members of the public | 12 | 34% |
| Science communicators (journalists, bloggers, editors) | 2 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 102 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 16% |
| Researcher | 15 | 15% |
| Student > Bachelor | 10 | 10% |
| Student > Master | 10 | 10% |
| Unspecified | 5 | 5% |
| Other | 12 | 12% |
| Unknown | 34 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 20 | 20% |
| Agricultural and Biological Sciences | 7 | 7% |
| Biochemistry, Genetics and Molecular Biology | 7 | 7% |
| Computer Science | 5 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 5% |
| Other | 19 | 19% |
| Unknown | 39 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. 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 18 November 2021.
All research outputs
#1,830,136
of 24,903,209 outputs
Outputs from Journal of Cheminformatics
#145
of 934 outputs
Outputs of similar age
#41,578
of 434,115 outputs
Outputs of similar age from Journal of Cheminformatics
#3
of 33 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% 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 done well, scoring higher than 84% 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 434,115 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.