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Blind trials of computer-assisted structure elucidation software

Overview of attention for article published in Journal of Cheminformatics, February 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

blogs
2 blogs
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7 X users
googleplus
1 Google+ user
linkedin
1 LinkedIn user

Citations

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22 Dimensions

Readers on

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40 Mendeley
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Title
Blind trials of computer-assisted structure elucidation software
Published in
Journal of Cheminformatics, February 2012
DOI 10.1186/1758-2946-4-5
Pubmed ID
Authors

Arvin Moser, Mikhail E Elyashberg, Antony J Williams, Kirill A Blinov, Joseph C DiMartino

Abstract

One of the largest challenges in chemistry today remains that of efficiently mining through vast amounts of data in order to elucidate the chemical structure for an unknown compound. The elucidated candidate compound must be fully consistent with the data and any other competing candidates efficiently eliminated without doubt by using additional data if necessary. It has become increasingly necessary to incorporate an in silico structure generation and verification tool to facilitate this elucidation process. An effective structure elucidation software technology aims to mimic the skills of a human in interpreting the complex nature of spectral data while producing a solution within a reasonable amount of time. This type of software is known as computer-assisted structure elucidation or CASE software. A systematic trial of the ACD/Structure Elucidator CASE software was conducted over an extended period of time by analysing a set of single and double-blind trials submitted by a global audience of scientists. The purpose of the blind trials was to reduce subjective bias. Double-blind trials comprised of data where the candidate compound was unknown to both the submitting scientist and the analyst. The level of expertise of the submitting scientist ranged from novice to expert structure elucidation specialists with experience in pharmaceutical, industrial, government and academic environments.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
French Polynesia 1 3%
Germany 1 3%
Netherlands 1 3%
Russia 1 3%
Japan 1 3%
United States 1 3%
Poland 1 3%
Unknown 33 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 35%
Student > Ph. D. Student 6 15%
Student > Bachelor 3 8%
Student > Master 3 8%
Lecturer 2 5%
Other 6 15%
Unknown 6 15%
Readers by discipline Count As %
Chemistry 22 55%
Agricultural and Biological Sciences 4 10%
Computer Science 2 5%
Biochemistry, Genetics and Molecular Biology 1 3%
Neuroscience 1 3%
Other 1 3%
Unknown 9 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 13 February 2019.
All research outputs
#1,902,789
of 24,903,209 outputs
Outputs from Journal of Cheminformatics
#154
of 934 outputs
Outputs of similar age
#14,111
of 258,771 outputs
Outputs of similar age from Journal of Cheminformatics
#2
of 7 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 934 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. 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 258,771 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 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.