rewire.it
Task

viral sequence detection

Viral sequence detection evaluates a classifier on temporally separated reference-genome collections.

SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

1 evaluation · 1 metric row

At a glance

Inputs, training, access and other details

Explanatory profile: limited source coverage · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.

Data, procedure and scoring
PropertyDescription and evidence
DatasetsNCBI viral RefSeq and prokaryotic-host reference sequences.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
SplitsThe downstream classifier uses earlier records for training, an intermediate period for validation and later records for testing.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
MetricsConfusion-matrix measures include recall, accuracy, precision and F1.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
BaselinesDeepVirFinder, PPR-Meta and CHEER on the temporal and CAMI marine test settings.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
Leakage controlsThe embedding stage uses the broader reference collection spanning the later evaluation period; downstream temporal separation alone is not an end-to-end temporal exclusion guarantee.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
UncertaintyThe cited text-accessible evaluation sections give no confidence-interval, resampling or repeat-run error-bar specification. Image-only tables and uninspected supplements are outside this absence claim. · Not reported in inspected sources
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
Entity typePaper-specific computational evaluation protocol.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
OrganismsViruses and prokaryotic hosts from NCBI reference sequences.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
AssaysReference-derived viral/nonviral labels.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
Allowed inputsNucleotide sequence fragments.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
AdaptationA downstream classifier uses temporal partitions; sequence embedding was trained on a broader corpus.
SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

How it works

How it worksComputational evaluation flow
Computational evaluation flow1. Input: Nucleotide sequence fragments.. Then: 2. Evaluation: A downstream classifier uses temporal partitions; sequence embedding was trained on a broader corpus.. Then: 3. Readout: Confusion-matrix measures include recall, accuracy, precision and F1.Computational evaluation flow1. Input: Nucleotide sequence fragments.. Then: 2. Evaluation: A downstream classifier uses temporal partitions; sequence embedding was trained on a broader corpus.. Then: 3. Readout: Confusion-matrix measures include recall, accuracy, precision and F1.Computational evaluation flow1. Input: Nucleotide sequence fragments.. Then: 2. Evaluation: A downstream classifier uses temporal partitions; sequence embedding was trained on a broader corpus.. Then: 3. Readout: Confusion-matrix measures include recall, accuracy, precision and F1.

Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol.

SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions
Evaluation methodology

NCBI viral RefSeq and prokaryotic-host reference sequences. The downstream classifier uses earlier records for training, an intermediate period for validation and later records for testing. Confusion-matrix measures include recall, accuracy, precision and F1. DeepVirFinder, PPR-Meta and CHEER on the temporal and CAMI marine test settings. The embedding stage uses the broader reference collection spanning the later evaluation period; downstream temporal separation alone is not an end-to-end temporal exclusion guarantee. The cited text-accessible evaluation sections give no confidence-interval, resampling or repeat-run error-bar specification. Image-only tables and uninspected supplements are outside this absence claim.

SourcesDETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Recorded evaluations

Each evaluation records what was tested and under which conditions.

Tested entities and results

Release 2026-09-17-d277315f7d76 · 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.

Papers and result coverage

Last literature check: 2026-09-17. Dated primary-source discovery and protocol/table screening. Source checking does not mean experimental reproduction. Only separately extracted and independently reviewed numeric batches are publishable.

Paper or primary resourceVersionReference
DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomesPMC archival version PMC10313334.1Read source

What is still missing

  • complete numerical transcription and independent cell review: Full primary artifact and table inventory preserved; no new numeric row is published from this audit alone.
  • exact checkpoint hashes and per-method scored denominators: Table labels alone do not establish these fields; do not infer checkpoint or scored count from model name or dataset size.
Search and extraction details

primary comparison tables located

Searches

  • DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes 10.3389/fmicb.2023.1169791

Evidence locations

  • Table 1; XML table T1
  • Table 2; XML table T2
  • Table 3; XML table T3

Strengths and limitations

Profile review details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Stable record: reported-task-3d4dec23120fef

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

18 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-17-d277315f7d76
Property and statementOriginal source and locationReview and provenance
Diagram caption

Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol.

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.diagram.caption

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Diagram steps

["Input: Nucleotide sequence fragments.","Evaluation: A downstream classifier uses temporal partitions; sequence embedding was trained on a broader corpus.","Readout: Confusion-matrix measures include recall, accuracy, precision and F1."]

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.diagram.steps

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Diagram title

Computational evaluation flow

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.diagram.title

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Datasets

NCBI viral RefSeq and prokaryotic-host reference sequences.

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.0.value

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Splits

The downstream classifier uses earlier records for training, an intermediate period for validation and later records for testing.

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.1.value

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Adaptation

A downstream classifier uses temporal partitions; sequence embedding was trained on a broader corpus.

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.10.value

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Metrics

Confusion-matrix measures include recall, accuracy, precision and F1.

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.2.value

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Baselines

DeepVirFinder, PPR-Meta and CHEER on the temporal and CAMI marine test settings.

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.3.value

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Leakage controls

The embedding stage uses the broader reference collection spanning the later evaluation period; downstream temporal separation alone is not an end-to-end temporal exclusion guarantee.

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.4.value

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Uncertainty

The cited text-accessible evaluation sections give no confidence-interval, resampling or repeat-run error-bar specification. Image-only tables and uninspected supplements are outside this absence claim.

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

Original source ↗

Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions

Version: PMC archival version PMC10313334.1
Retrieved: 2026-09-16T10:33:58.392Z

unreported

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.5.value

Source artifact SHA-256: 9ff7d32758620f7b0b0628425f62abff103ca2e33269ce3763383584bcebfc3c

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Sources and history

Release 2026-09-17-d277315f7d76 · Record review: needs review

2 source records and release historyDownload this release
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.
benchmark research
review date: 2026-09-17; status: primary_comparison_tables_located; primary sources: evidence-expansion-detire-viral-metagenomes-2023-9ff7d327; inspected locators: Table 1; XML table T1; Table 2; XML table T2; Table 3; XML table T3; searched queries: DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes 10.3389/fmicb.2023.1169791; gaps: complete numerical transcription and independent cell review: Full primary artifact and table inventory preserved; no new numeric row is published from this audit alone.; exact checkpoint hashes and per-method scored denominators: Table labels alone do not establish these fields; do not infer checkpoint or scored count from model name or dataset size.; claim scope: Dated primary-source discovery and protocol/table screening. Source checking does not mean experimental reproduction. Only separately extracted and independently reviewed numeric batches are publishable.
historical missing metadata
protocol version: not_reported_in_legacy_extract
metadata review scope
historical_missing_metadata preserves the original discovery state. Current descriptive evidence and missingness are recorded in profile.facts; numerical-result review is separate.
legacy kinds
benchmark
entity classification
review date: 2026-09-17; rationale: This source-scoped record identifies the biological prediction task and holds its paper context. Preserve the existing task identity; exact split, model adaptation and scoring remain in linked evaluations or separate protocol records.; source ids: detire-viral-metagenomes-2023; source locator: Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions; ambiguities: A paper- or suite-specific task may constrain some inputs or metrics; that alone does not make it interchangeable with a complete versioned protocol. No protocol equivalence is inferred.; Some legacy profile Entity type facts use the generic phrase computational evaluation protocol. That boilerplate is not sufficient to establish a single fixed protocol identity or to merge this task with another protocol record.
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