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Expert-augmented machine learning

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, February 2020
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
186 X users
facebook
1 Facebook page

Citations

dimensions_citation
75 Dimensions

Readers on

mendeley
247 Mendeley
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Title
Expert-augmented machine learning
Published in
Proceedings of the National Academy of Sciences of the United States of America, February 2020
DOI 10.1073/pnas.1906831117
Pubmed ID
Authors

Efstathios D. Gennatas, Jerome H. Friedman, Lyle H. Ungar, Romain Pirracchio, Eric Eaton, Lara G. Reichmann, Yannet Interian, José Marcio Luna, Charles B. Simone, Andrew Auerbach, Elier Delgado, Mark J. van der Laan, Timothy D. Solberg, Gilmer Valdes

X Demographics

X Demographics

The data shown below were collected from the profiles of 186 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 247 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 247 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 48 19%
Student > Ph. D. Student 44 18%
Student > Master 16 6%
Student > Doctoral Student 14 6%
Student > Bachelor 11 4%
Other 34 14%
Unknown 80 32%
Readers by discipline Count As %
Computer Science 43 17%
Medicine and Dentistry 18 7%
Engineering 17 7%
Agricultural and Biological Sciences 9 4%
Chemistry 6 2%
Other 59 24%
Unknown 95 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 104. 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 20 January 2022.
All research outputs
#411,718
of 25,708,267 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#7,356
of 103,588 outputs
Outputs of similar age
#10,698
of 383,967 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#143
of 932 outputs
Altmetric has tracked 25,708,267 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 103,588 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.6. This one has done particularly well, scoring higher than 92% 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 383,967 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 932 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.