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Mendeley readers
| Title |
Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: application to North American waterfowl
|
|---|---|
| Published in |
Movement Ecology, May 2022
|
| DOI | 10.1186/s40462-022-00324-7 |
| Pubmed ID | |
| Authors |
Cory Overton, Michael Casazza, Joseph Bretz, Fiona McDuie, Elliott Matchett, Desmond Mackell, Austen Lorenz, Andrea Mott, Mark Herzog, Josh Ackerman |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 24% |
| Professor > Associate Professor | 3 | 14% |
| Researcher | 3 | 14% |
| Student > Doctoral Student | 2 | 10% |
| Other | 2 | 10% |
| Other | 1 | 5% |
| Unknown | 5 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 48% |
| Computer Science | 3 | 14% |
| Nursing and Health Professions | 1 | 5% |
| Environmental Science | 1 | 5% |
| Business, Management and Accounting | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 5 | 24% |