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A Machine Learning Approach to the Observation Operator for Satellite Radiance Data Assimilation

Overview of attention for article published in Journal of the Meteorological Society of Japan, February 2023
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
2 X users
facebook
1 Facebook page

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
10 Mendeley
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Title
A Machine Learning Approach to the Observation Operator for Satellite Radiance Data Assimilation
Published in
Journal of the Meteorological Society of Japan, February 2023
DOI 10.2151/jmsj.2023-005
Authors

Jianyu LIANG, Koji TERASAKI, Takemasa MIYOSHI

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 3 30%
Student > Doctoral Student 2 20%
Researcher 2 20%
Student > Ph. D. Student 1 10%
Unknown 2 20%
Readers by discipline Count As %
Unspecified 3 30%
Earth and Planetary Sciences 3 30%
Arts and Humanities 1 10%
Engineering 1 10%
Unknown 2 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 13 March 2023.
All research outputs
#17,094,640
of 25,899,121 outputs
Outputs from Journal of the Meteorological Society of Japan
#712
of 1,033 outputs
Outputs of similar age
#263,901
of 485,850 outputs
Outputs of similar age from Journal of the Meteorological Society of Japan
#4
of 9 outputs
Altmetric has tracked 25,899,121 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,033 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 23rd percentile – i.e., 23% 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 485,850 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.