Title |
WorMachine: machine learning-based phenotypic analysis tool for worms
|
---|---|
Published by |
Springer Nature, January 2018
|
DOI | 10.1186/s12915-017-0477-0 |
Pubmed ID | |
Authors |
Adam Hakim, Yael Mor, Itai Antoine Toker, Amir Levine, Moran Neuhof, Yishai Markovitz, Oded Rechavi |
X Demographics
The data shown below were collected from the profiles of 45 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 | 8 | 18% |
Israel | 3 | 7% |
United Kingdom | 3 | 7% |
Canada | 2 | 4% |
Belgium | 1 | 2% |
Austria | 1 | 2% |
India | 1 | 2% |
Germany | 1 | 2% |
Unknown | 25 | 56% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 25 | 56% |
Scientists | 17 | 38% |
Science communicators (journalists, bloggers, editors) | 3 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 74 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 13 | 18% |
Student > Bachelor | 11 | 15% |
Researcher | 10 | 14% |
Student > Ph. D. Student | 8 | 11% |
Professor > Associate Professor | 3 | 4% |
Other | 9 | 12% |
Unknown | 20 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 15 | 20% |
Agricultural and Biological Sciences | 12 | 16% |
Engineering | 5 | 7% |
Medicine and Dentistry | 4 | 5% |
Computer Science | 3 | 4% |
Other | 13 | 18% |
Unknown | 22 | 30% |