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X Demographics
Mendeley readers
Title |
A Methodology for Evaluating Operator Usage of Machine Learning Recommendations for Power Grid Contingency Analysis
|
---|---|
Published in |
Frontiers in Big Data, June 2022
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DOI | 10.3389/fdata.2022.897295 |
Pubmed ID | |
Authors |
John Wenskovitch, Brett Jefferson, Alexander Anderson, Jessica Baweja, Danielle Ciesielski, Corey Fallon |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 75% |
Switzerland | 1 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 50% |
Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 13 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Unspecified | 4 | 31% |
Student > Master | 2 | 15% |
Student > Ph. D. Student | 1 | 8% |
Student > Bachelor | 1 | 8% |
Professor > Associate Professor | 1 | 8% |
Other | 0 | 0% |
Unknown | 4 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Unspecified | 4 | 31% |
Chemical Engineering | 1 | 8% |
Environmental Science | 1 | 8% |
Computer Science | 1 | 8% |
Psychology | 1 | 8% |
Other | 0 | 0% |
Unknown | 5 | 38% |