source · discovered

Retentive Network promotes efficient RNA language modeling of long sequences

Primary paper retained with its original identifier. Metadata inherited from the literature collection; individual result checks are separate.

Sources and history

Release 2026-09-16-d74d282221a9 · Record review: discovered

No supporting source is linked yet.

Technical metadata and extraction receipts

Stable ID: rnaret-2026

areas: rna-transcriptomes
url: https://pmc.ncbi.nlm.nih.gov/articles/PMC13111708/
version: journal full text in PMC
retrieved at: 2026-09-15T23:33:26Z
doi: 10.1038/s42003-026-09757-x
publication status: peer_reviewed
year: 2026
artifact sha256: e970e7322e07fb3c9d12efd315691cc5de5575a3f2616f4b788614c8c706dd0b
artifact url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13111708/fullTextXML
artifact retrieved at: 2026-09-16T10:38:57.558224+00:00
legacy paper: id: rnaret-2026; title: Retentive Network promotes efficient RNA language modeling of long sequences; year: 2026; publication status: peer_reviewed; version: journal full text in PMC; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC13111708/; primary domain: rna-transcriptomes; retrieved utc: 2026-09-15T23:33:26Z; doi: 10.1038/s42003-026-09757-x; notes: Numeric result checked against Table 1 in primary full-text XML; journal/source: Communications Biology.
scope decision: included
missing metadata: licence: not_reported_in_legacy_extract

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