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Machine Learning to Classify Suicidal Thoughts and Behaviors: Implementation Within the Common Data Elements Used by the Military Suicide Research Consortium

Overview of attention for article published in Clinical Psychological Science, March 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
35 Mendeley
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Title
Machine Learning to Classify Suicidal Thoughts and Behaviors: Implementation Within the Common Data Elements Used by the Military Suicide Research Consortium
Published in
Clinical Psychological Science, March 2021
DOI 10.1177/2167702620961067
Authors

Andrew K. Littlefield, Jeffrey T. Cooke, Courtney L. Bagge, Catherine R. Glenn, Evan M. Kleiman, Ross Jacobucci, Alexander J. Millner, Douglas Steinley

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 14%
Researcher 4 11%
Student > Bachelor 3 9%
Professor 2 6%
Student > Master 2 6%
Other 2 6%
Unknown 17 49%
Readers by discipline Count As %
Psychology 10 29%
Business, Management and Accounting 1 3%
Computer Science 1 3%
Physics and Astronomy 1 3%
Social Sciences 1 3%
Other 2 6%
Unknown 19 54%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 04 May 2021.
All research outputs
#3,366,374
of 23,301,510 outputs
Outputs from Clinical Psychological Science
#613
of 787 outputs
Outputs of similar age
#87,766
of 425,163 outputs
Outputs of similar age from Clinical Psychological Science
#43
of 55 outputs
Altmetric has tracked 23,301,510 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 787 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 47.3. This one is in the 13th percentile – i.e., 13% 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 425,163 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 79% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.