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Nodal solutions for Neumann systems with gradient dependence

Overview of attention for article published in Boundary Value Problems, January 2024
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  • Among the highest-scoring outputs from this source (#45 of 166)
  • Average Attention Score compared to outputs of the same age

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Title
Nodal solutions for Neumann systems with gradient dependence
Published in
Boundary Value Problems, January 2024
DOI 10.1186/s13661-023-01814-2
URN
urn:issn:1687-2770
Authors

Kamel Saoudi, Eadah Alzahrani, Dušan D. Repovš

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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 11 January 2024.
All research outputs
#19,962,154
of 25,394,764 outputs
Outputs from Boundary Value Problems
#45
of 166 outputs
Outputs of similar age
#217,048
of 332,188 outputs
Outputs of similar age from Boundary Value Problems
#1
of 1 outputs
Altmetric has tracked 25,394,764 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 166 research outputs from this source. They receive a mean Attention Score of 1.3. This one has gotten more attention than average, scoring higher than 69% 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 332,188 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 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