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Multinomial N-Mixture Models Improve the Applicability of Electrofishing for Developing Population Estimates of Stream-Dwelling Smallmouth Bass

Overview of attention for article published in North American Journal of Fisheries Management, January 2017
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Mentioned by

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1 tweeter

Citations

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10 Dimensions

Readers on

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28 Mendeley
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Title
Multinomial N-Mixture Models Improve the Applicability of Electrofishing for Developing Population Estimates of Stream-Dwelling Smallmouth Bass
Published in
North American Journal of Fisheries Management, January 2017
DOI 10.1080/02755947.2016.1254127
Authors

Robert Mollenhauer, Shannon K. Brewer

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 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 %
Researcher 8 29%
Student > Ph. D. Student 7 25%
Student > Master 6 21%
Student > Bachelor 2 7%
Other 1 4%
Other 1 4%
Unknown 3 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 46%
Environmental Science 9 32%
Unknown 6 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 January 2017.
All research outputs
#6,785,107
of 8,903,958 outputs
Outputs from North American Journal of Fisheries Management
#306
of 389 outputs
Outputs of similar age
#214,388
of 302,141 outputs
Outputs of similar age from North American Journal of Fisheries Management
#9
of 15 outputs
Altmetric has tracked 8,903,958 research outputs across all sources so far. This one is in the 13th percentile – i.e., 13% of other outputs scored the same or lower than it.
So far Altmetric has tracked 389 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 4th percentile – i.e., 4% 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 302,141 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.