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Deciding Univariate Polynomial Problems Using Untrusted Certificates in Isabelle/HOL

Overview of attention for article published in Journal of Automated Reasoning, August 2017
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3 X users

Citations

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4 Mendeley
Title
Deciding Univariate Polynomial Problems Using Untrusted Certificates in Isabelle/HOL
Published in
Journal of Automated Reasoning, August 2017
DOI 10.1007/s10817-017-9424-6
Authors

Wenda Li, Grant Olney Passmore, Lawrence C. Paulson

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 25%
Unknown 3 75%
Readers by discipline Count As %
Computer Science 1 25%
Unknown 3 75%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 12 April 2018.
All research outputs
#18,833,474
of 24,002,307 outputs
Outputs from Journal of Automated Reasoning
#109
of 140 outputs
Outputs of similar age
#232,704
of 320,780 outputs
Outputs of similar age from Journal of Automated Reasoning
#3
of 3 outputs
Altmetric has tracked 24,002,307 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 140 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 22nd percentile – i.e., 22% 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 320,780 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.