| Typicality: | 0.472 |
| Saliency: | 0.369 |
| in this study | 4 | location |
| to calculate proportionate levels of risk | 4 | purpose |
| to predict missed etas | 3 | purpose |
| model → use → machine learning | 26 |
| model → use → machine learning techniques | 7 |
| model → use → machine learning algorithms | 4 |
| model → use → machine learning methods | 4 |
| negative | neutral | positive |
| 0.022 | 0.615 | 0.363 |
| Raw frequency | 41 |
| Normalized frequency | 0.369 |
| Modifier score | 0.700 |
| Perplexity | 156.388 |