Model type
Study-specific predictive method; this record is the paper-specific evaluated configuration.
Configuration
ICCTax
ICCTax adapts HyenaDNA for hierarchical taxonomic classification across four superkingdoms.
Sources
ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · Abstract (paragraph 1); 3 Experiments/3.2 Experiments on ICCTax performance/3.2.2 Performance on the complete dataset (paragraph 2)How it worksEvaluated procedure (conceptual)
Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings.
Sources
ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1)At a glance
Biological inputs
1,500-bp metagenomic contigs
Sources
ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 3 Experiments/3.6 Taxonomic profiling on real metagenomic data (paragraph 1); 2 Methods (paragraph 1)Outputs
Hierarchical taxonomic assignments, including 155 genera and 43 phyla in the study
Sources
ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · Abstract (paragraph 1); 1 Introduction (paragraph 6)limited source coverage · Automated source review, 2026-09-16. All specifications and missing details
Evaluations and results
Release 2026-09-17-d277315f7d76 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| ICCTax: Hierarchical metagenomic taxonomy classification Configuration: ICCTaxTask: Hierarchical metagenomic taxonomy classificationDataset: ICCTax Complete dataset Macro average precision at genus rank on Complete dataset. Author-reported evaluation · Evaluation metadata: needs review | ||
| 67.20 Genus macro AveP Unit: % · Direction: unknown | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkedICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · Table 2, ICCTax row, Genus column Source checking is not independent reproduction. |
How it works
How the evaluated method works
HyenaDNA sequence features feed complementary-view hierarchical metric learning, with a hierarchical compactness loss and outputs linked across taxonomic levels.
Sources
ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1)What was evaluated
The linked evaluation record identifies ICCTax: Hierarchical metagenomic taxonomy classification. Its dataset, split, adaptation and evidence origin remain attached to the reported results.
Sources
ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · The named evaluation’s methods and comparison table; exact preserved evaluation IDs: evaluation-lit-b3-035Strengths and limitations
Strengths and considerations
- Explicitly evaluates imbalanced and out-of-distribution taxonomic settings.
Sources
ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 2 Methods/2.3 Compactness loss (paragraph 2); 2 Methods/2.2 Complementary-view based hierarchical metric learning (paragraph 3)
Limitations and conditions
- The trained taxonomy and sequence sampling define the classifier’s coverage; unobserved labels are not automatically identifiable.
Sources
ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 3 Experiments/3.1 Datasets (paragraph 1); 2 Methods/2.3 Compactness loss (paragraph 2)
Profile review details
Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction.
Stable record: reported-model-67eaf766fa9877Specifications
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 |
|---|---|
| Model type | Study-specific predictive method; this record is the paper-specific evaluated configuration.SourcesICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1) |
| Architecture / procedure | HyenaDNA sequence features feed complementary-view hierarchical metric learning, with a hierarchical compactness loss and outputs linked across taxonomic levels.SourcesICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1) |
| Biological inputs | 1,500-bp metagenomic contigsSourcesICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 3 Experiments/3.6 Taxonomic profiling on real metagenomic data (paragraph 1); 2 Methods (paragraph 1) |
| Outputs | Hierarchical taxonomic assignments, including 155 genera and 43 phyla in the studySourcesICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · Abstract (paragraph 1); 1 Introduction (paragraph 6) |
| Parameters | An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sourcesSources (2)ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model; Ying-Lab/ICCTax README.md · 2 Methods; 2 Methods/2.1 HyenaDNA; 2 Methods/2.2 Complementary-view based hierarchical metric learning; 2 Methods/2.3 Compactness loss; 2 Methods/2.4 Total loss function; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision |
| Known versions / configuration | ICCTax is the comparison-table label; that label does not specify an immutable weight revision. · Not reported in inspected sourcesSourcesICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label. |
| Training data / fitting | Models use ID, OOD and Complete genomic datasets constructed from 1,500-bp fragments of archaea, bacteria, eukaryotes andviruses. The Complete-trained classifier is then applied to external marine,16S and wastewater datasets.SourcesICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 3 Experiments/3.1 Datasets (paragraph 1); Abstract (paragraph 1) |
| Context limits | 1,500-bp trimmed contigs in the evaluated pipeline.SourcesICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · 3 Experiments/3.6 Taxonomic profiling on real metagenomic data (paragraph 1); 2 Methods (paragraph 1) |
| Access | Official study implementation and usage documentation: https://github.com/Ying-Lab/ICCTax/blob/6b7381c7111bde6d40324cd033501204bf3ac3bc/README.md. This pinned documentation revision is not automatically the evaluated weight revision.SourcesYing-Lab/ICCTax README.md · README.md; installation, model download and usage instructions |
| Code licence | No explicit code licence was established from the paper’s availability statement and inspected repository-root documentation. · Not reported in inspected sourcesSourcesYing-Lab/ICCTax README.md · README.md and repository-root licence-file search |
| Weights licence | The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. · Not reported in inspected sourcesSourcesYing-Lab/ICCTax README.md · README.md; checkpoint/access documentation and licence scope |
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.
20 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Diagram caption Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings. Individual claims | ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram steps ["1,500-bp metagenomic contigs","ICCTax","Hierarchical taxonomic assignments, including 155 genera and 43 phyla in the study"] Individual claims | ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Evaluated procedure (conceptual) Individual claims | ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Model type Study-specific predictive method; this record is the paper-specific evaluated configuration. Individual claims | ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Architecture / procedure HyenaDNA sequence features feed complementary-view hierarchical metric learning, with a hierarchical compactness loss and outputs linked across taxonomic levels. Individual claims | ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Weights licence The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. Individual claims | Ying-Lab/ICCTax README.md README.md; checkpoint/access documentation and licence scope Version: 6b7381c7111bde6d40324cd033501204bf3ac3bc | unreported automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Biological inputs 1,500-bp metagenomic contigs Individual claims | ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model 3 Experiments/3.6 Taxonomic profiling on real metagenomic data (paragraph 1); 2 Methods (paragraph 1) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Outputs Hierarchical taxonomic assignments, including 155 genera and 43 phyla in the study Individual claims | ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model Abstract (paragraph 1); 1 Introduction (paragraph 6) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims | Ying-Lab/ICCTax README.md 2 Methods; 2 Methods/2.1 HyenaDNA; 2 Methods/2.2 Complementary-view based hierarchical metric learning; 2 Methods/2.3 Compactness loss; 2 Methods/2.4 Total loss function; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6b7381c7111bde6d40324cd033501204bf3ac3bc | unreported automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims | ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model 2 Methods; 2 Methods/2.1 HyenaDNA; 2 Methods/2.2 Complementary-view based hierarchical metric learning; 2 Methods/2.3 Compactness loss; 2 Methods/2.4 Total loss function; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: version of record | unreported automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-09-17-d277315f7d76 · Record review: needs review
2 source records and release history
- ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model · Original source · version of record
- Ying-Lab/ICCTax README.md · Original source · 6b7381c7111bde6d40324cd033501204bf3ac3bc
Technical metadata and extraction receipts
Stable ID: reported-model-67eaf766fa9877
- areas
- microbes-communities
- entity level
- method
- version
- Not reported
- reported name
- ICCTax
- historical missing metadata
- version: not_reported_in_legacy_extract; checkpoint revision: not_reported_in_legacy_extract; training data: not_reported_in_legacy_extract; licence: 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
- model
- entity classification
- review date: 2026-09-17; rationale: This source-scoped entry preserves the method/configuration actually named in an evaluation. It is neither a global family identity nor proof of an immutable checkpoint; the linked evaluation retains adaptation, fitting and scoring details.; source ids: icctax-2025; source locator: 3 Experiments/3.4 Model analysis of ICCTax/3.4.2 Ablation study (paragraph 2); 2 Methods/2.4 Total loss function (paragraph 1) | Abstract (paragraph 1); 3 Experiments/3.2 Experiments on ICCTax performance/3.2.2 Performance on the complete dataset (paragraph 2); ambiguities: Configuration means the source-labelled evaluated identity. It does not establish missing checkpoint hashes, default settings or equivalence to same-named records in other papers.