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Lessons Learned from Multiobjective Automatic Optimizations of Classical Three-Site Rigid Water Models Using Microscopic and Macroscopic Target Experimental Observables

Overview of attention for article published in Journal of Chemical & Engineering Data, December 2023
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#17 of 1,467)
  • High Attention Score compared to outputs of the same age (89th percentile)

Mentioned by

twitter
18 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
4 Mendeley
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Title
Lessons Learned from Multiobjective Automatic Optimizations of Classical Three-Site Rigid Water Models Using Microscopic and Macroscopic Target Experimental Observables
Published in
Journal of Chemical & Engineering Data, December 2023
DOI 10.1021/acs.jced.3c00538
Authors

Mattia Perrone, Riccardo Capelli, Charly Empereur-mot, Ali Hassanali, Giovanni M. Pavan

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 %
Unspecified 1 25%
Professor 1 25%
Researcher 1 25%
Unknown 1 25%
Readers by discipline Count As %
Chemistry 2 50%
Unspecified 1 25%
Unknown 1 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 2023.
All research outputs
#2,523,482
of 24,963,265 outputs
Outputs from Journal of Chemical & Engineering Data
#17
of 1,467 outputs
Outputs of similar age
#18,571
of 180,729 outputs
Outputs of similar age from Journal of Chemical & Engineering Data
#1
of 3 outputs
Altmetric has tracked 24,963,265 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,467 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 98% 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 180,729 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
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. This one has scored higher than all of them