Eta shows interesting results in these settings. As a dispersion-based measure, we expected Eta to effectively identify an artificial word as distinctive, especially when the word is evenly spread across a high number of segments. However, as the number of segments containing the artificial word increases, its scores remain consistently low compared to randomly assigned words. Only in a scenario with one occurrence in 1000 segments does the artificial word receive the first rank (Fig. 3). This indicates that Hypothesis 4 is supported solely by both variants of Zeta and the rank-sum test.