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Localized Defect Detection from Spatially Mapped, In-Situ Process Data With Machine Learning

Overview of attention for article published in Frontiers in Mechanical Engineering, November 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
27 Mendeley
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Title
Localized Defect Detection from Spatially Mapped, In-Situ Process Data With Machine Learning
Published in
Frontiers in Mechanical Engineering, November 2021
DOI 10.3389/fmech.2021.767444
Authors

William Halsey, Derek Rose, Luke Scime, Ryan Dehoff, Vincent Paquit

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 19%
Student > Ph. D. Student 4 15%
Researcher 2 7%
Other 1 4%
Student > Bachelor 1 4%
Other 1 4%
Unknown 13 48%
Readers by discipline Count As %
Engineering 8 30%
Computer Science 3 11%
Materials Science 1 4%
Unknown 15 56%
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 19 November 2021.
All research outputs
#14,268,548
of 23,310,485 outputs
Outputs from Frontiers in Mechanical Engineering
#107
of 514 outputs
Outputs of similar age
#201,421
of 428,173 outputs
Outputs of similar age from Frontiers in Mechanical Engineering
#2
of 23 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 514 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done well, scoring higher than 77% 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 428,173 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 51% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.