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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
1 X user
bluesky
1 Bluesky user

Readers on

mendeley
32 Mendeley
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Article details
Title
Machine learning approach for high-throughput phenolic antioxidant screening in black Rice germplasm collection based on surface FTIR
Published in
Food Chemistry, August 2024
DOI 10.1016/j.foodchem.2024.140728
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Unspecified 4 13%
Lecturer > Senior Lecturer 2 6%
Lecturer 2 6%
Professor > Associate Professor 2 6%
Researcher 1 3%
Other 3 9%
Unknown 18 56%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 5 16%
Unspecified 4 13%
Chemistry 2 6%
Engineering 2 6%
Business, Management and Accounting 1 3%
Other 1 3%
Unknown 17 53%
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 09 December 2024.
All research outputs
#17,587,432
of 27,380,387 outputs
Outputs from Food Chemistry
#6,466
of 12,557 outputs
Outputs of similar age
#135,022
of 304,244 outputs
Outputs of similar age from Food Chemistry
#29
of 129 outputs
Altmetric has tracked 27,380,387 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,557 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 47th percentile – i.e., 47% 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 304,244 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 129 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.