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In this paper we propose a new Word Sense Induction (WSI) method and apply it to construct a solution for theRuShiftEval shared task on Lexical Semantic Change Detection (LSCD) for the Russian language. Our WSI algorithm based on lexical substitution achieves stateoftheart performance for the Russian language on the RUSSE2018 dataset. However, our LSCD system based on it has shown poor performance in the shared task. We havestudied mathematical properties of the COMPARE score employed in the task for measuring the degree of semanticchange, as well as the discrepancies between this score and our WSI predictions. We have found that our methodcan detect those aspects of semantic change, which the COMPARE metric is not sensitive to, such as appearance ordisappearance of a rare word sense. An important property of our method is its interpretability, which we exploitto perform the detailed error analysis