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Michigan Publishing

Canvass: A Crowd-Sourced, Natural-Product Screening Library for Exploring Biological Space

Overview of attention for article published in ACS Central Science, December 2018
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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 (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

twitter
66 X users

Citations

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32 Dimensions

Readers on

mendeley
108 Mendeley
Title
Canvass: A Crowd-Sourced, Natural-Product Screening Library for Exploring Biological Space
Published in
ACS Central Science, December 2018
DOI 10.1021/acscentsci.8b00747
Pubmed ID
Authors

Sara E. Kearney, Gergely Zahoránszky-Kőhalmi, Kyle R. Brimacombe, Mark J. Henderson, Caitlin Lynch, Tongan Zhao, Kanny K. Wan, Zina Itkin, Christopher Dillon, Min Shen, Dorian M. Cheff, Tobie D. Lee, Danielle Bougie, Ken Cheng, Nathan P. Coussens, Dorjbal Dorjsuren, Richard T. Eastman, Ruili Huang, Michael J. Iannotti, Surendra Karavadhi, Carleen Klumpp-Thomas, Jacob S. Roth, Srilatha Sakamuru, Wei Sun, Steven A. Titus, Adam Yasgar, Ya-Qin Zhang, Jinghua Zhao, Rodrigo B. Andrade, M. Kevin Brown, Noah Z. Burns, Jin K. Cha, Emily E. Mevers, Jon Clardy, Jason A. Clement, Peter A. Crooks, Gregory D. Cuny, Jake Ganor, Jesus Moreno, Lucas A. Morrill, Elias Picazo, Robert B. Susick, Neil K. Garg, Brian C. Goess, Robert B. Grossman, Chambers C. Hughes, Jeffrey N. Johnston, Madeleine M. Joullie, A. Douglas Kinghorn, David G.I. Kingston, Michael J. Krische, Ohyun Kwon, Thomas J. Maimone, Susruta Majumdar, Katherine N. Maloney, Enas Mohamed, Brian T. Murphy, Pavel Nagorny, David E. Olson, Larry E. Overman, Lauren E. Brown, John K. Snyder, John A. Porco, Fatima Rivas, Samir A. Ross, Richmond Sarpong, Indrajeet Sharma, Jared T. Shaw, Zhengren Xu, Ben Shen, Wei Shi, Corey R.J. Stephenson, Alyssa L. Verano, Derek S. Tan, Yi Tang, Richard E. Taylor, Regan J. Thomson, David A. Vosburg, Jimmy Wu, William M. Wuest, Armen Zakarian, Yufeng Zhang, Tianjing Ren, Zhong Zuo, James Inglese, Sam Michael, Anton Simeonov, Wei Zheng, Paul Shinn, Ajit Jadhav, Matthew B. Boxer, Matthew D. Hall, Menghang Xia, Rajarshi Guha, Jason M. Rohde

X Demographics

X Demographics

The data shown below were collected from the profiles of 66 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 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 108 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 21%
Researcher 17 16%
Student > Master 9 8%
Professor 8 7%
Professor > Associate Professor 6 6%
Other 21 19%
Unknown 24 22%
Readers by discipline Count As %
Chemistry 36 33%
Biochemistry, Genetics and Molecular Biology 13 12%
Agricultural and Biological Sciences 6 6%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Medicine and Dentistry 3 3%
Other 16 15%
Unknown 30 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 38. 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 05 May 2020.
All research outputs
#1,084,813
of 25,641,627 outputs
Outputs from ACS Central Science
#314
of 1,940 outputs
Outputs of similar age
#24,396
of 447,513 outputs
Outputs of similar age from ACS Central Science
#12
of 57 outputs
Altmetric has tracked 25,641,627 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 1,940 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 30.8. This one has done well, scoring higher than 83% 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 447,513 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 94% of its contemporaries.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.