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Mendeley readers
Attention Score in Context
Title |
Estimation of diffusion coefficients from voltammetric signals by support vector and gaussian process regression
|
---|---|
Published in |
Journal of Cheminformatics, May 2014
|
DOI | 10.1186/1758-2946-6-30 |
Pubmed ID | |
Authors |
Martin Bogdan, Dominik Brugger, Wolfgang Rosenstiel, Bernd Speiser |
Abstract |
Support vector regression (SVR) and Gaussian process regression (GPR) were used for the analysis of electroanalytical experimental data to estimate diffusion coefficients. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
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 % |
---|---|---|
Korea, Republic of | 1 | <1% |
Unknown | 101 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 24 | 24% |
Student > Bachelor | 13 | 13% |
Student > Master | 9 | 9% |
Student > Doctoral Student | 5 | 5% |
Researcher | 5 | 5% |
Other | 9 | 9% |
Unknown | 37 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 34 | 33% |
Materials Science | 6 | 6% |
Chemical Engineering | 5 | 5% |
Engineering | 4 | 4% |
Unspecified | 3 | 3% |
Other | 9 | 9% |
Unknown | 41 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 23 October 2019.
All research outputs
#6,940,770
of 22,757,541 outputs
Outputs from Journal of Cheminformatics
#560
of 828 outputs
Outputs of similar age
#66,404
of 226,672 outputs
Outputs of similar age from Journal of Cheminformatics
#6
of 22 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 828 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 31st percentile – i.e., 31% 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 226,672 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 69% of its contemporaries.
We're also able to compare this research output to 22 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.