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A per-cent-level determination of the nucleon axial coupling from quantum chromodynamics

Overview of attention for article published in Nature, May 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

13 news outlets
3 blogs
36 tweeters
1 Facebook page
1 Google+ user


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46 Mendeley
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A per-cent-level determination of the nucleon axial coupling from quantum chromodynamics
Published in
Nature, May 2018
DOI 10.1038/s41586-018-0161-8
Pubmed ID

C. C. Chang, A. N. Nicholson, E. Rinaldi, E. Berkowitz, N. Garron, D. A. Brantley, H. Monge-Camacho, C. J. Monahan, C. Bouchard, M. A. Clark, B. Joó, T. Kurth, K. Orginos, P. Vranas, A. Walker-Loud


The axial coupling of the nucleon, gA, is the strength of its coupling to the weak axial current of the standard model of particle physics, in much the same way as the electric charge is the strength of the coupling to the electromagnetic current. This axial coupling dictates the rate at which neutrons decay to protons, the strength of the attractive long-range force between nucleons and other features of nuclear physics. Precision tests of the standard model in nuclear environments require a quantitative understanding of nuclear physics that is rooted in quantum chromodynamics, a pillar of the standard model. The importance of gA makes it a benchmark quantity to determine theoretically-a difficult task because quantum chromodynamics is non-perturbative, precluding known analytical methods. Lattice quantum chromodynamics provides a rigorous, non-perturbative definition of quantum chromodynamics that can be implemented numerically. It has been estimated that a precision of two per cent would be possible by 2020 if two challenges are overcome1,2: contamination of gA from excited states must be controlled in the calculations and statistical precision must be improved markedly2-10. Here we use an unconventional method 11 inspired by the Feynman-Hellmann theorem that overcomes these challenges. We calculate a gA value of 1.271 ± 0.013, which has a precision of about one per cent.

Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 36 tweeters 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 26%
Student > Ph. D. Student 10 22%
Student > Doctoral Student 5 11%
Student > Master 5 11%
Professor > Associate Professor 3 7%
Other 6 13%
Unknown 5 11%
Readers by discipline Count As %
Physics and Astronomy 28 61%
Engineering 2 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Biochemistry, Genetics and Molecular Biology 1 2%
Immunology and Microbiology 1 2%
Other 3 7%
Unknown 10 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 130. 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 19 August 2019.
All research outputs
of 23,332,901 outputs
Outputs from Nature
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Outputs of similar age
of 331,818 outputs
Outputs of similar age from Nature
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Altmetric has tracked 23,332,901 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 92,097 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 100.1. This one has done well, scoring higher than 83% 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 331,818 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 934 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 62% of its contemporaries.