source · discovered

DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes

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

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

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Technical metadata and extraction receipts

Stable ID: detire-viral-metagenomes-2023

areas: microbes-communities
url: https://pmc.ncbi.nlm.nih.gov/articles/PMC10313334/
version: PMC archival version PMC10313334.1
retrieved at: 2026-09-15T23:37:05Z
doi: 10.3389/fmicb.2023.1169791
publication status: peer_reviewed
year: 2023
artifact sha256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c
artifact url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC10313334/fullTextXML
artifact retrieved at: 2026-09-16T10:33:58.392Z
legacy paper: id: detire-viral-metagenomes-2023; title: DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes; year: 2023; publication status: peer_reviewed; version: PMC archival version PMC10313334.1; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC10313334/; primary domain: microbes-communities; retrieved utc: 2026-09-15T23:37:05Z; notes: Primary full text verified via Europe PMC fullTextXML; venue: Frontiers in Microbiology; PMC ID: PMC10313334. Task-specific viral classifier, included as a microbial metagenomics benchmark.; doi: 10.3389/fmicb.2023.1169791
scope decision: included
missing metadata: licence: not_reported_in_legacy_extract

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