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Representable Markov categories and comparison of statistical experiments in categorical probability

Overview of attention for article published in Theoretical Computer Science, June 2023
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#17 of 1,937)
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
30 X users

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
19 Mendeley
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Title
Representable Markov categories and comparison of statistical experiments in categorical probability
Published in
Theoretical Computer Science, June 2023
DOI 10.1016/j.tcs.2023.113896
Authors

Tobias Fritz, Tomáš Gonda, Paolo Perrone, Eigil Fjeldgren Rischel

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 30 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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 16%
Researcher 3 16%
Professor 2 11%
Student > Master 2 11%
Unknown 9 47%
Readers by discipline Count As %
Computer Science 6 32%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Mathematics 1 5%
Physics and Astronomy 1 5%
Decision Sciences 1 5%
Other 1 5%
Unknown 8 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 May 2023.
All research outputs
#2,283,952
of 26,745,262 outputs
Outputs from Theoretical Computer Science
#17
of 1,937 outputs
Outputs of similar age
#43,404
of 402,366 outputs
Outputs of similar age from Theoretical Computer Science
#1
of 6 outputs
Altmetric has tracked 26,745,262 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,937 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done particularly well, scoring higher than 99% 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 402,366 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 89% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them