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Interpretable machine learning to identify important predictors of birth weight: A prospective cohort study

Overview of attention for article published in Frontiers in Pediatrics, November 2022
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  • Average Attention Score compared to outputs of the same age and source

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2 X users

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32 Mendeley
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Title
Interpretable machine learning to identify important predictors of birth weight: A prospective cohort study
Published in
Frontiers in Pediatrics, November 2022
DOI 10.3389/fped.2022.899954
Pubmed ID
Authors

Zheng Liu, Na Han, Tao Su, Yuelong Ji, Heling Bao, Shuang Zhou, Shusheng Luo, Hui Wang, Jue Liu, Hai-Jun Wang

Timeline

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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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
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

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 16%
Student > Ph. D. Student 3 9%
Professor > Associate Professor 3 9%
Student > Bachelor 3 9%
Other 2 6%
Other 7 22%
Unknown 9 28%
Readers by discipline Count As %
Medicine and Dentistry 7 22%
Nursing and Health Professions 4 13%
Engineering 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Mathematics 1 3%
Other 4 13%
Unknown 11 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 18 December 2022.
All research outputs
#18,860,161
of 23,372,207 outputs
Outputs from Frontiers in Pediatrics
#3,523
of 6,340 outputs
Outputs of similar age
#305,946
of 441,185 outputs
Outputs of similar age from Frontiers in Pediatrics
#205
of 460 outputs
Altmetric has tracked 23,372,207 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,340 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one is in the 31st percentile – i.e., 31% 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 441,185 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 460 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.