↓ Skip to main content

Predictive Analysis Using Chemical-Gene Interaction Networks Consistent with Observed Endocrine Activity and Mutagenicity of U.S. Streams

Overview of attention for article published in Environmental Science & Technology, July 2019
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 X users

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
28 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Predictive Analysis Using Chemical-Gene Interaction Networks Consistent with Observed Endocrine Activity and Mutagenicity of U.S. Streams
Published in
Environmental Science & Technology, July 2019
DOI 10.1021/acs.est.9b02990
Pubmed ID
Authors

Jason P. Berninger, David M. DeMarini, Sarah H. Warren, Jane Ellen Simmons, Vickie S. Wilson, Justin M. Conley, Mikayla D. Armstrong, Luke R. Iwanowicz, Dana W. Kolpin, Kathryn M. Kuivila, Timothy J. Reilly, Kristin M. Romanok, Daniel L. Villeneuve, Paul M. Bradley

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 32%
Researcher 3 11%
Lecturer 2 7%
Student > Bachelor 2 7%
Student > Master 2 7%
Other 2 7%
Unknown 8 29%
Readers by discipline Count As %
Environmental Science 4 14%
Biochemistry, Genetics and Molecular Biology 3 11%
Business, Management and Accounting 2 7%
Agricultural and Biological Sciences 2 7%
Engineering 2 7%
Other 2 7%
Unknown 13 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 17 July 2019.
All research outputs
#16,728,456
of 25,385,509 outputs
Outputs from Environmental Science & Technology
#16,483
of 20,682 outputs
Outputs of similar age
#217,825
of 360,226 outputs
Outputs of similar age from Environmental Science & Technology
#175
of 242 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,682 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.8. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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 360,226 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 242 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.