Reference change · event page

Efficient generative modeling of protein sequences using simple autoregressive models.Nature Communications, 12:5800, 2021

Published notice on a work cited in the Pith corpus. Exact quotes below. No model judges whether any citation was load-bearing.

This page records that a citing paper's bibliography includes a work with a published notice. It is not a judgment on the citing paper.

Correction Crossref 1 open · 1 total · 0 disputed

DOI: 10.1038/s41467-021-25756-4
Notice DOI: 10.1038/s41467-022-29593-x
Event date: 2022-04-01
Machine twin: JSON

01One-hop citing occurrences

Correction Open

Training-Free Generation of Protein Sequences from Small Family Alignments via Stochastic Attention

ref [9] · 2603.14717 · notice #7864 · dispute

Raw extraction · bibliography line

Jeanne Trinquier, Guido Uguzzoni, Andrea Pagnani, Francesco Zamponi, and Martin Weigt. Efficient generative modeling of protein sequences using simple autoregressive models.Nature Communications, 12:5800, 2021. doi: 10.1038/s41467-021-25756-4

Status lifecycle on notices: open → disputed → (response attached on the notice page). Repaired counts matter as much as open counts. There is no “safe,” “invalid,” or “resolved” badge.