The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
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Timeline
X Demographics
Mendeley readers
| Title |
Interpretability Versus Accuracy: A Comparison of Machine Learning Models Built Using Different Algorithms, Performance Measures, and Features to Predict E. coli Levels in Agricultural Water
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, May 2021
|
| DOI | 10.3389/frai.2021.628441 |
| Pubmed ID | |
| Authors |
Daniel L. Weller, Tanzy M. T. Love, Martin Wiedmann |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 67% |
| Switzerland | 1 | 8% |
| Unknown | 3 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 67% |
| Scientists | 3 | 25% |
| Practitioners (doctors, other healthcare professionals) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 54 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 17% |
| Researcher | 6 | 11% |
| Student > Master | 4 | 7% |
| Lecturer | 3 | 6% |
| Student > Bachelor | 2 | 4% |
| Other | 9 | 17% |
| Unknown | 21 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 9 | 17% |
| Computer Science | 6 | 11% |
| Agricultural and Biological Sciences | 5 | 9% |
| Unspecified | 2 | 4% |
| Medicine and Dentistry | 2 | 4% |
| Other | 6 | 11% |
| Unknown | 24 | 44% |