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X Demographics
Mendeley readers
| Title |
Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, June 2021
|
| DOI | 10.3389/frai.2021.576892 |
| Pubmed ID | |
| Authors |
Shailesh Tripathi, David Muhr, Manuel Brunner, Herbert Jodlbauer, Matthias Dehmer, Frank Emmert-Streib |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 93 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 11% |
| Researcher | 8 | 9% |
| Student > Ph. D. Student | 7 | 8% |
| Student > Bachelor | 6 | 6% |
| Student > Doctoral Student | 3 | 3% |
| Other | 11 | 12% |
| Unknown | 48 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 20 | 22% |
| Computer Science | 14 | 15% |
| Business, Management and Accounting | 2 | 2% |
| Physics and Astronomy | 2 | 2% |
| Arts and Humanities | 1 | 1% |
| Other | 3 | 3% |
| Unknown | 51 | 55% |