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Article Metrics

Automated detection of Mycobacterial growth on 96-well plates for rapid and accurate Tuberculosis drug susceptibility testing

Overview of attention for article published in bioRxiv, December 2017
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
46 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
13 Mendeley
Title
Automated detection of Mycobacterial growth on 96-well plates for rapid and accurate Tuberculosis drug susceptibility testing
Published in
bioRxiv, December 2017
DOI 10.1101/229427
Authors

Philip W Fowler, Ana L Gilbertoni Cruz, Sarah J Hoosdally, Lisa Jarrett, Emanuele Borroni, Matteo Chiacchiaretta, Priti Rathod, Timothy M Walker, Esther Robinson, Timothy EA Peto, Daniela M. Cirillo, E Grace Smith, Derrick W Crook, Ana Luiza Gibertoni Cruz, Daniela Maria M. Cirillo, Ana Luíza Gibertoni Cruz, Daniela Maria Cirillo

Twitter Demographics

The data shown below were collected from the profiles of 46 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 31%
Unspecified 3 23%
Other 2 15%
Student > Master 2 15%
Researcher 1 8%
Other 1 8%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 31%
Unspecified 3 23%
Immunology and Microbiology 2 15%
Agricultural and Biological Sciences 2 15%
Pharmacology, Toxicology and Pharmaceutical Science 1 8%
Other 1 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 10 January 2018.
All research outputs
#540,872
of 12,301,494 outputs
Outputs from bioRxiv
#4,738
of 38,542 outputs
Outputs of similar age
#26,248
of 346,020 outputs
Outputs of similar age from bioRxiv
#495
of 3,395 outputs
Altmetric has tracked 12,301,494 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 38,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has done well, scoring higher than 87% 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 346,020 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 92% of its contemporaries.
We're also able to compare this research output to 3,395 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.