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benchmark · task

viral sequence detection

This paper-specific evaluation tests viral sequence detection using testing viral metagenome dataset.

1 evaluations · 1 metric rows

At a glance

Explanatory profile: limited source coverage · Automated source review, 2026-09-16. This does not change the review status of its results.

Data, procedure and scoring
PropertyDescription and evidence
Record typePaper-specific task; protocol incompletely extractedDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Table 1, Accuracy row, DETIRE column
Inputstesting viral metagenome datasetDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Table 1, Accuracy row, DETIRE column
AssessmentaccuracyDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Table 1, Accuracy row, DETIRE column
Recorded split or evaluation settingtestDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Table 1, Accuracy row, DETIRE column
DatasetsNot extracted or verified for this record.
OrganismsNot extracted or verified for this record.
AssaysNot extracted or verified for this record.
AdaptationNot extracted or verified for this record.
BaselinesNot extracted or verified for this record.

How it works

Reported evaluation outline

Outline of the existing paper extraction. Split membership, fitting details and scorer implementation remain incompletely reviewed.

Reported evaluation outlinetesting viral metagenome dataset. Then: Recorded fitting or scoring procedure. Then: Assess accuracytesting viral metagenome datasetRecorded fitting or scoringprocedureAssess accuracy
Read the diagram as text
  1. testing viral metagenome dataset
  2. Recorded fitting or scoring procedure
  3. Assess accuracy
DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Table 1, Accuracy row, DETIRE column

Evaluation context

The existing paper extraction describes: Hybrid deep learning virus-fragment classifier on paper testing dataset. This description is retained with the exact evaluation records; it is not a new protocol reconstruction.

DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Table 1, Accuracy row, DETIRE column

Tested models and results

Release 2026-09-16-d74d282221a9 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.

Results grouped by the exact reported evaluation
Metric and findingCoverage and uncertaintyEvidence
DETIRE: viral sequence detection

Hybrid deep learning virus-fragment classifier on paper testing dataset

Author-reported evaluation · Evaluation metadata: needs review

0.8772 accuracy

Unit: fraction · Direction: unknown

Uncertainty: not reported in legacy extract

Scored: Not reported · Eligible: Not reported

source checkedDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Table 1, Accuracy row, DETIRE column

Source checking is not independent reproduction.

Strengths and limitations

Profile review details

Catalogue extraction inspected; protocol claims remain limited to the cited evidence. Missing details are not presumed absent from the original paper.

Stable record: reported-task-3d4dec23120fef

Sources and history

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

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Technical metadata and extraction receipts

Stable ID: reported-task-3d4dec23120fef

areas
microbes-communities
tasks
viral sequence detection
entity level
task
version
Not reported
task
viral sequence detection
scope note
Paper-specific evaluation task; protocol completeness requires further extraction.
missing metadata
protocol version: not_reported_in_legacy_extract
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