This makes evaluating confidence in novel peptide identifications more difficult. NovoBoard has proposed a solution using decoy spectra to set a lower-bound on FDR, as had been established in spectral library search approaches . Moreover, several other postprocessing tools have emerged to refine de novo sequencing results: pNovo3 incorporates fragment ion intensity predictions, Spectralis applies Levenshtein distance metrics, PostNovo combines multiple sequencing methods to rescore predictions, SMSNet improves low-confidence predictions with a peptide database, and Instanovo+ includes a diffusion-based decoder to refine sequences. Although these tools all help quantify confidence, no validated method currently exists to set an FDR threshold with strong statistical support, or to compare confidence levels across different de novo tools, complicating their integration into broader workflows.