In the second setting, the artificial word's frequency was fixed at 1000 occurrences, but its dispersion varied. The idea was again to isolate one parameter, in this case dispersion, and analyze its influence on the performance of measures. The dispersion experiment involved different numbers of segments receiving the artificial word with specified frequencies, leading to 20 parameter settings. In the comparison corpus, scenarios included 1 segment with 1000 words and 1000 segments with 1 word. For each of these parameters, we conducted distinctiveness analyses with variations in the target corpus (the first number refers to the number of segments that receive the artificial word, and the second to how many times the artificial word is included in each of the selected segments): 1/1000, 2/500, 5/200, 10/100, 20/50, 50/20, 100/10, 200/5, 500/2, 1000/1. <hi xmlns="http://www.tei-c.org/ns/1.0" rend="italic">Pydistinto</hi> was again run 100 times for each parameter setting.