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Machine learning applied to simulations of collisions between rotating, differentiated planets

Overview of attention for article published in Computational Astrophysics and Cosmology, December 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
17 Mendeley
Title
Machine learning applied to simulations of collisions between rotating, differentiated planets
Published in
Computational Astrophysics and Cosmology, December 2020
DOI 10.1186/s40668-020-00034-6
Authors

Miles L. Timpe, Maria Han Veiga, Mischa Knabenhans, Joachim Stadel, Stefano Marelli

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 29%
Student > Bachelor 2 12%
Student > Doctoral Student 2 12%
Professor 2 12%
Other 1 6%
Other 3 18%
Unknown 2 12%
Readers by discipline Count As %
Physics and Astronomy 9 53%
Earth and Planetary Sciences 2 12%
Business, Management and Accounting 1 6%
Nursing and Health Professions 1 6%
Engineering 1 6%
Other 0 0%
Unknown 3 18%

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 08 December 2020.
All research outputs
#5,636,166
of 17,896,489 outputs
Outputs from Computational Astrophysics and Cosmology
#18
of 24 outputs
Outputs of similar age
#163,098
of 416,335 outputs
Outputs of similar age from Computational Astrophysics and Cosmology
#2
of 2 outputs
Altmetric has tracked 17,896,489 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 24 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 42.8. This one scored the same or higher as 6 of them.
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 416,335 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 60% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.