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SMARTA: Automated testing apparatus for visual discrimination tasks

Overview of attention for article published in Behavior Research Methods, September 2018
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
1 blog
twitter
27 tweeters
facebook
1 Facebook page

Readers on

mendeley
3 Mendeley
Title
SMARTA: Automated testing apparatus for visual discrimination tasks
Published in
Behavior Research Methods, September 2018
DOI 10.3758/s13428-018-1113-9
Pubmed ID
Authors

Raymond Vagell, Vance J. Vagell, Rachel L. Jacobs, James Gordon, Andrea L. Baden

Abstract

This article introduces the open-source Subject-Mediated Automatic Remote Testing Apparatus (SMARTA) for visual discrimination tasks, which aims to streamline and ease data collection, eliminate or reduce observer error, increase interobserver agreement, and automate data entry without the need for an internet connection. SMARTA is inexpensive and easy to build, and it can be modified to accommodate a variety of experimental designs. Here we describe the utility and functionality of SMARTA in a captive setting. We present the results from a case study of color vision in ruffed lemurs (Varecia spp.) at the Duke Lemur Center in Durham, North Carolina, in which we demonstrate SMARTA's utility for two-choice color discrimination tasks, as well as its ability to streamline and standardize data collection. We also include detailed instructions for constructing and implementing the fully integrated SMARTA touchscreen system.

Twitter Demographics

The data shown below were collected from the profiles of 27 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 33%
Unknown 2 67%
Readers by discipline Count As %
Computer Science 1 33%
Unknown 2 67%

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 26 November 2019.
All research outputs
#738,687
of 14,083,883 outputs
Outputs from Behavior Research Methods
#66
of 1,190 outputs
Outputs of similar age
#25,238
of 271,080 outputs
Outputs of similar age from Behavior Research Methods
#2
of 56 outputs
Altmetric has tracked 14,083,883 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,190 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done particularly well, scoring higher than 94% 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 271,080 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 90% of its contemporaries.
We're also able to compare this research output to 56 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 96% of its contemporaries.