Analyzing the frequency-based measures such as the chi-square test, LLR, and RRF, we observe a tendency for the score to increase with increasing frequency, but there are notable differences among the various measures (Fig. 2). When the artificial word reaches a frequency of 200 or higher in the target corpus, its RRF rank is consistently 1, indicating that it achieves the highest score among all words in the corpus. This observation aligns with our earlier analysis conducted without the artificial word (Fig. 1). Notably, RRF scores of 10 or below (corresponding to a frequency of 100 words in the target corpus) fail to achieve the first rank. This also explains the wide distribution of ranks observed for RRF scores based on a frequency of 100 words in the target corpus. Regarding the LLR and chi-squared tests, both measures are even more sensitive to frequency variation compared to RRF. At a frequency of 40 and higher, we observe the artificial word achieving the first rank. TF-IDF shows moderate sensitivity to frequency variation, partially supporting Hypothesis 5.