Model type
Logistic-regression pipeline; this record is the paper-specific evaluated configuration.
Pipeline
PC-mer + LR
PC-mer plus logistic regression is a physicochemical-sequence-feature baseline for bacterial taxonomy.
Sources
PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 3 Results/3.5 PC-mer in use by the metagenomics ML-based classifier/3.5.2 Execution times (paragraph 1); 1 Introduction (paragraph 6)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
PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1)At a glance
Biological inputs
DNA/RNA sequence-derived physicochemical feature vectors
Sources
PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 2 Method/2.1 Feature extraction method (paragraph 1); 4. Discussion (paragraph 3)Outputs
Taxonomic class labels
Sources
PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 3 Results/3.1 Datasets (paragraph 1); 2 Method (paragraph 1)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 |
|---|---|---|
| PC-mer + LR: metagenomic genus classification k=8 PC-mer feature extraction with logistic regression on AMP genus-classification dataset Author-reported evaluation · Evaluation metadata: needs review | ||
| 96.95% accuracy Unit: percent · Direction: unknown | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkedPC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · Table 3, AMP section, PC-mer + LR k=8 row, Accuracy (%) column Source checking is not independent reproduction. |
How it works
How the evaluated method works
PC-mer encodes nucleotide physicochemical properties in a feature vector, followed by a fitted logistic-regression classifier.
Sources
PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1)What was evaluated
The linked evaluation record identifies PC-mer + LR: metagenomic genus classification. Its dataset, split, adaptation and evidence origin remain attached to the reported results.
Sources
PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · The named evaluation’s methods and comparison table; exact preserved evaluation IDs: evaluation-lit-b4-019Strengths and limitations
Strengths and considerations
- Provides a comparatively simple fitted classifier to test whether complex pretrained models outperform structured sequence statistics.
Sources
PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 3 Results/3.5 PC-mer in use by the metagenomics ML-based classifier (paragraph 1); 2 Method/2.2 Learning unit (paragraph 1)
Limitations and conditions
- The feature dimension, k setting and taxonomic label set belong to the evaluated dataset; headline results across taxonomic levels are not interchangeable.
Sources
PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 3 Results/3.5 PC-mer in use by the metagenomics ML-based classifier/3.5.1 Training and testing procedure (paragraph 1); 3 Results/3.4 Feature extraction capability of PC-mer (paragraph 1)
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-688eb780ef7d2eSpecifications
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 | Logistic-regression pipeline; this record is the paper-specific evaluated configuration.SourcesPC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1) |
| Architecture / procedure | PC-mer encodes nucleotide physicochemical properties in a feature vector, followed by a fitted logistic-regression classifier.SourcesPC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1) |
| Biological inputs | DNA/RNA sequence-derived physicochemical feature vectorsSourcesPC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 2 Method/2.1 Feature extraction method (paragraph 1); 4. Discussion (paragraph 3) |
| Outputs | Taxonomic class labelsSourcesPC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 3 Results/3.1 Datasets (paragraph 1); 2 Method (paragraph 1) |
| Parameters | An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sourcesSources (2)PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification; SAkbari93/PC-mer_Metagenomics README.md · 2 Method; 2 Method/2.1 Feature extraction method; 2 Method/2.2 Learning unit; 3 Results/3.3 PC-mer in use by distance-based methods for comparison and classifying metagenomics sequences; 3 Results/3.5 PC-mer in use by the metagenomics ML-based classifier/3.5.1 Training and testing procedure; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision |
| Known versions / configuration | PC-mer + LR is the comparison-table label; that label does not specify an immutable weight revision. · Not reported in inspected sourcesSourcesPC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label. |
| Training data / fitting | A ten-fold study compares feature transformations and eight classifiers on AMP/shotgun metagenomic datasets. The balanced HTL dataset includes 1,000 sequences from 100 genera; a separate unbalanced Qiita-derived dataset supports species-level analysis.SourcesPC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · 3 Results/3.1 Datasets (paragraph 1); 3 Results/3.5 PC-mer in use by the metagenomics ML-based classifier/3.5.1 Training and testing procedure (paragraph 1) |
| Context limits | A maximum input/context length for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sourcesSources (2)PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification; SAkbari93/PC-mer_Metagenomics README.md · 2 Method; 2 Method/2.1 Feature extraction method; 2 Method/2.2 Learning unit; 3 Results/3.3 PC-mer in use by distance-based methods for comparison and classifying metagenomics sequences; 3 Results/3.5 PC-mer in use by the metagenomics ML-based classifier/3.5.1 Training and testing procedure; inspected for explicit maximum input length (dataset lengths and family-wide limits are not substituted); README.md at pinned repository revision |
| Access | Official study implementation and usage documentation: https://github.com/SAkbari93/PC-mer_Metagenomics/blob/5c5f89dcaec5098372ad1fe82d4215186fe417c1/README.md. This pinned documentation revision is not automatically the evaluated weight revision.SourcesSAkbari93/PC-mer_Metagenomics 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 sourcesSourcesSAkbari93/PC-mer_Metagenomics 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 sourcesSourcesSAkbari93/PC-mer_Metagenomics 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.
21 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 | PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification 2 Method/2.2 Learning unit (paragraph 1); 2 Method (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 ["DNA/RNA sequence-derived physicochemical feature vectors","PC-mer + LR","Taxonomic class labels"] Individual claims | PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification 2 Method/2.2 Learning unit (paragraph 1); 2 Method (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 | PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification 2 Method/2.2 Learning unit (paragraph 1); 2 Method (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 Logistic-regression pipeline; this record is the paper-specific evaluated configuration. Individual claims | PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification 2 Method/2.2 Learning unit (paragraph 1); 2 Method (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 PC-mer encodes nucleotide physicochemical properties in a feature vector, followed by a fitted logistic-regression classifier. Individual claims | PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification 2 Method/2.2 Learning unit (paragraph 1); 2 Method (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 | SAkbari93/PC-mer_Metagenomics README.md README.md; checkpoint/access documentation and licence scope Version: 5c5f89dcaec5098372ad1fe82d4215186fe417c1 | 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 DNA/RNA sequence-derived physicochemical feature vectors Individual claims | PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification 2 Method/2.1 Feature extraction method (paragraph 1); 4. Discussion (paragraph 3) 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 Taxonomic class labels Individual claims | PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification 3 Results/3.1 Datasets (paragraph 1); 2 Method (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 |
| Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims | SAkbari93/PC-mer_Metagenomics README.md 2 Method; 2 Method/2.1 Feature extraction method; 2 Method/2.2 Learning unit; 3 Results/3.3 PC-mer in use by distance-based methods for comparison and classifying metagenomics sequences; 3 Results/3.5 PC-mer in use by the metagenomics ML-based classifier/3.5.1 Training and testing procedure; 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: 5c5f89dcaec5098372ad1fe82d4215186fe417c1 | 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 | PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification 2 Method; 2 Method/2.1 Feature extraction method; 2 Method/2.2 Learning unit; 3 Results/3.3 PC-mer in use by distance-based methods for comparison and classifying metagenomics sequences; 3 Results/3.5 PC-mer in use by the metagenomics ML-based classifier/3.5.1 Training and testing procedure; 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
- PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification · Original source · version of record
- SAkbari93/PC-mer_Metagenomics README.md · Original source · 5c5f89dcaec5098372ad1fe82d4215186fe417c1
Technical metadata and extraction receipts
Stable ID: reported-model-688eb780ef7d2e
- areas
- microbes-communities
- entity level
- method
- version
- Not reported
- reported name
- PC-mer + LR
- 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: The source explicitly separates PC-mer sequence preprocessing/feature generation from the fitted learning unit; this evaluated composition uses logistic regression. Preserve the exact source-scoped composition and its results; no additional checkpoint or family equivalence is inferred.; source ids: pc-mer-2024; source locator: 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1) | 3 Results/3.5 PC-mer in use by the metagenomics ML-based classifier/3.5.2 Execution times (paragraph 1); 1 Introduction (paragraph 6) | Methods 2.1 feature extraction and 2.2 Learning unit; Figure 1 pipeline; ambiguities: This is the paper-specific pipeline identity. Missing component versions or checkpoint hashes remain unknown; a shared upstream name does not establish equivalent pipelines.