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Coupling Machine Learning and High Throughput Multiplex Digital PCR Enables Accurate Detection of Carbapenem-Resistant Genes in Clinical Isolates

Overview of attention for article published in Frontiers in Molecular Biosciences, November 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 (78th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

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Citations

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Readers on

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24 Mendeley
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Title
Coupling Machine Learning and High Throughput Multiplex Digital PCR Enables Accurate Detection of Carbapenem-Resistant Genes in Clinical Isolates
Published in
Frontiers in Molecular Biosciences, November 2021
DOI 10.3389/fmolb.2021.775299
Pubmed ID
Authors

Luca Miglietta, Ahmad Moniri, Ivana Pennisi, Kenny Malpartida-Cardenas, Hala Abbas, Kerri Hill-Cawthorne, Frances Bolt, Elita Jauneikaite, Frances Davies, Alison Holmes, Pantelis Georgiou, Jesus Rodriguez-Manzano

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X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 25%
Researcher 3 13%
Unspecified 1 4%
Professor > Associate Professor 1 4%
Other 1 4%
Other 0 0%
Unknown 12 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 33%
Agricultural and Biological Sciences 2 8%
Unspecified 1 4%
Computer Science 1 4%
Medicine and Dentistry 1 4%
Other 0 0%
Unknown 11 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 06 December 2021.
All research outputs
#4,577,274
of 23,310,485 outputs
Outputs from Frontiers in Molecular Biosciences
#402
of 4,002 outputs
Outputs of similar age
#110,474
of 510,402 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#28
of 365 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,002 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 89% 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 510,402 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 78% of its contemporaries.
We're also able to compare this research output to 365 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.