We therefore engaged in the design of MS2DECIDE, a decision theory-based tool that aggregates the annotations of GNPS, Sirius and ISDB-LOTUS and produces a recommendation concerning the potential novelty of a compound (Fig. ). Our approach consists in designing a function k that associates a "knownness" score to each candidate ion: the highest that score, the greater the chance that a similar compound has been reported in a database. MS2DECIDE then simply ranks the candidate ions by order of decreasing score.