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Mendeley readers
Attention Score in Context
Title |
Ycasd– a tool for capturing and scaling data from graphical representations
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Published in |
BMC Bioinformatics, June 2014
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DOI | 10.1186/1471-2105-15-219 |
Pubmed ID | |
Authors |
Arnd Gross, Sibylle Schirm, Markus Scholz |
Abstract |
Mathematical modelling of biological processes often requires a large variety of different data sets for parameter estimation and validation. It is common practice that clinical data are not available in raw formats but are provided as graphical representations. Hence, in order to include these data into environments used for model simulations and statistical analyses, it is necessary to extract them from their presentations in the literature. For this purpose, we developed the freely available open source tool ycasd. After establishing a coordinate system by simple axes definitions, it supports convenient retrieval of data points from arbitrary figures. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Norway | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 36 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 10 | 28% |
Student > Ph. D. Student | 6 | 17% |
Student > Master | 5 | 14% |
Student > Bachelor | 4 | 11% |
Professor | 4 | 11% |
Other | 3 | 8% |
Unknown | 4 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 7 | 19% |
Agricultural and Biological Sciences | 7 | 19% |
Medicine and Dentistry | 6 | 17% |
Sports and Recreations | 3 | 8% |
Linguistics | 2 | 6% |
Other | 7 | 19% |
Unknown | 4 | 11% |
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 26 December 2023.
All research outputs
#7,822,127
of 25,058,309 outputs
Outputs from BMC Bioinformatics
#2,855
of 7,642 outputs
Outputs of similar age
#69,743
of 233,889 outputs
Outputs of similar age from BMC Bioinformatics
#51
of 152 outputs
Altmetric has tracked 25,058,309 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,642 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 60% 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 233,889 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 68% of its contemporaries.
We're also able to compare this research output to 152 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 64% of its contemporaries.