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Timeline
X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Loss-Function Learning for Digital Tissue Deconvolution
|
---|---|
Chapter number | 5 |
Book title |
Research in Computational Molecular Biology
|
Published in |
arXiv, January 2018
|
DOI | 10.1007/978-3-319-89929-9_5 |
Book ISBNs |
978-3-31-989928-2, 978-3-31-989929-9
|
Authors |
Franziska Görtler, Stefan Solbrig, Tilo Wettig, Peter J. Oefner, Rainer Spang, Michael Altenbuchinger, Görtler, Franziska, Solbrig, Stefan, Wettig, Tilo, Oefner, Peter J., Spang, Rainer, Altenbuchinger, Michael |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 3 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 8 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 2 | 25% |
Student > Ph. D. Student | 1 | 13% |
Other | 1 | 13% |
Student > Master | 1 | 13% |
Unknown | 3 | 38% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 2 | 25% |
Medicine and Dentistry | 2 | 25% |
Engineering | 1 | 13% |
Unknown | 3 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 28 January 2018.
All research outputs
#16,005,008
of 24,355,571 outputs
Outputs from arXiv
#353,915
of 1,034,710 outputs
Outputs of similar age
#265,377
of 451,033 outputs
Outputs of similar age from arXiv
#9,134
of 21,611 outputs
Altmetric has tracked 24,355,571 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,034,710 research outputs from this source. They receive a mean Attention Score of 4.0. 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 451,033 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21,611 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 50% of its contemporaries.