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Attention Score in Context
Title |
Linear and nonlinear Dirichlet–Neumann methods in multiple subdomains for the Cahn–Hilliard equation
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Published in |
International Journal of Computer Mathematics, October 2023
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DOI | 10.1080/00207160.2023.2266068 |
Authors |
Gobinda Garai, Bankim C. Mandal |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
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 04 November 2023.
All research outputs
#16,889,961
of 24,833,004 outputs
Outputs from International Journal of Computer Mathematics
#88
of 180 outputs
Outputs of similar age
#159,830
of 303,050 outputs
Outputs of similar age from International Journal of Computer Mathematics
#2
of 2 outputs
Altmetric has tracked 24,833,004 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 180 research outputs from this source. They receive a mean Attention Score of 1.9. This one is in the 39th percentile – i.e., 39% 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 303,050 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
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.