Datasets
NCBI viral RefSeq and prokaryotic-host reference sequences.
Task
viral sequence detection
Viral sequence detection evaluates a classifier on temporally separated reference-genome collections.
Sources
DETIRE: 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 captionsOverview
Metrics
Confusion-matrix measures include recall, accuracy, precision and F1.
Allowed inputs
Nucleotide sequence fragments.
Sources
DETIRE: 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 captionsEvaluation procedure diagram
How it worksComputational evaluation flow
Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol.
Sources
DETIRE: 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 captionslimited source coverage · Automated source review, 2026-09-16. All specifications and missing details
Results
Results are available, but no reviewed comparison panel is linked in this release.
All evaluations
1 evaluation · 1 result. Different protocols are not a single leaderboard.
Filter evaluations
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: DETIRE | Task: viral sequence detection Dataset: testing viral metagenome dataset | 0.877 accuracy fraction · unknown Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDETIRE: viral sequence detection Hybrid deep learning virus-fragment classifier on paper testing dataset Aggregation: Not reported DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Table 1, Accuracy row, DETIRE column |
Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.
Methods and evaluation design
Procedure, tasks and evaluated configurations
How it works
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.
Sources
DETIRE: 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 captionsRecorded evaluations
Each evaluation records what was tested and under which conditions.
Run instructions
No runnable recipe has been reviewed for this task. Dataset access, model requirements, licences and compute requirements must be checked against its sources before execution.
A task describes a biological question. Choose a linked protocol to obtain concrete split and scoring instructions.
Strengths, limitations and unresolved questions
Strengths and limitations
Strengths and considerations
- Temporal classifier partitions expose distribution shift, while the source permits an explicit check of broader embedding-training overlap.
Sources
DETIRE: 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
Limitations and conditions
- This profile covers detection evaluation only. Exact reference overlap and comparator database versions remain unextracted.
Sources
DETIRE: 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
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-3d4dec23120fefSpecifications
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.
| Property | Description and evidence |
|---|---|
| Datasets | NCBI 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 |
| Splits | The 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 |
| Metrics | Confusion-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 |
| Baselines | DeepVirFinder, 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 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.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 |
| 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. · Not reported in inspected sourcesSourcesDETIRE: 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 type | Paper-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 |
| Organisms | Viruses 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 |
| Assays | Reference-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 inputs | Nucleotide 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 |
| Adaptation | A 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 |
Evidence
Source checking verifies the cited claim or transcription. It does not establish 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 resource | Version | Reference |
|---|---|---|
| DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes | PMC archival version PMC10313334.1 | Read source |
Historical gaps recorded on 2026-09-17
The catalogue now holds 1 result rows for this benchmark. A note below about pending extraction describes the state on 2026-09-17 and may since have been answered by a later batch. The result rows and their sources are the current record.
- 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
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
| Property and statement | Original source and location | Review 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 Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions Version: PMC archival version PMC10313334.1 | source checked automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Diagram steps
| DETIRE: 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 Version: PMC archival version PMC10313334.1 | source checked automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Computational evaluation flow Individual claims | DETIRE: 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 Version: PMC archival version PMC10313334.1 | source checked automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Datasets NCBI viral RefSeq and prokaryotic-host reference sequences. Individual claims | DETIRE: 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 Version: PMC archival version PMC10313334.1 | source checked automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions Version: PMC archival version PMC10313334.1 | source checked automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions Version: PMC archival version PMC10313334.1 | source checked automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Metrics Confusion-matrix measures include recall, accuracy, precision and F1. Individual claims | DETIRE: 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 Version: PMC archival version PMC10313334.1 | source checked automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions Version: PMC archival version PMC10313334.1 | source checked automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions Version: PMC archival version PMC10313334.1 | source checked automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 Methods §§2.1, 2.3; cached text lines 11–12, 19–20; matching task comparison table/ablation captions Version: PMC archival version PMC10313334.1 | unreported automated source review · 2026-09-16 Audit detailsTask-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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
View linked audit checks and correction history
Release 2026-09-29-06401fd5b220 · Record review: needs review
2 source records and release history
- DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Original source · PMC archival version PMC10313334.1
- DETIRE: a hybrid deep learning model for identifying viral sequences from metagenomes · Original source · PMC archival version PMC10313334.1
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.
Related records
- dataset: testing viral metagenome dataset
- benchmark: DETIRE: viral sequence detection