Open-world fungal ITS embeddings improve higher-rank placement and cross-view retrieval, but percent identity is stronger on a matched ITS2 novelty benchmark

1.

Background

Fungal internal transcribed spacer (ITS) analyses usually infer taxonomy and novelty from similarity to homologous reference sequences. Percent identity is a strong signal in that setting, but it cannot directly compare non-homologous barcode views and does not explicitly optimize the higher-rank placement of genera absent from the reference collection. We asked whether a compact sequence encoder could learn that open-world structure and whether maximum embedding cosine similarity could improve novelty detection. 2.