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)

1 evaluation · 1 result

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)

Overview

Model type

Logistic-regression pipeline; this record is the paper-specific evaluated configuration.

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)

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)

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.

Sources

SAkbari93/PC-mer_Metagenomics README.md · README.md; installation, model download and usage instructions

limited source coverage · Automated source review, 2026-09-16. All specifications and missing details

Evaluations and results

1 evaluation · 1 result. Different protocols are not a single leaderboard.

Filter evaluations

Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Pipeline: PC-mer + LR	Task: metagenomic genus classification Dataset: AMP	97% accuracy percent · unknown Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source PC-mer + LR: metagenomic genus classification k=8 PC-mer feature extraction with logistic regression on AMP genus-classification dataset Aggregation: Not reported PC-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. Release 2026-09-29-06401fd5b220.

Use this model

How it works, versions and access

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-b4-019

Strengths, limitations and unresolved questions

Strengths 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-688eb780ef7d2e

Specifications

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.

Inputs, outputs and configuration
Property	Description and evidence
Model type	Logistic-regression pipeline; this record is the paper-specific evaluated configuration. 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)
Architecture / procedure	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)
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)
Parameters	An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sources Sources (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 sources Sources PC-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. Sources PC-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 sources Sources (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. Sources SAkbari93/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 sources Sources SAkbari93/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 sources Sources SAkbari93/PC-mer_Metagenomics README.md · README.md; checkpoint/access documentation and licence scope

Evidence

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

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

Claims, original sources and review scope · Release 2026-09-29-06401fd5b220
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 Original source ↗ 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1) Version: version of record Retrieved: 2026-09-16T10:41:06Z	source checked automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `0b0a225fa6f5f3ba41dffc7b320c91f47738301cf45835260eecaa03b704a097` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1) Version: version of record Retrieved: 2026-09-16T10:41:06Z	source checked automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.diagram.steps` Source artifact SHA-256: `0b0a225fa6f5f3ba41dffc7b320c91f47738301cf45835260eecaa03b704a097` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram title Evaluated procedure (conceptual) Individual claims	PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification Original source ↗ 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1) Version: version of record Retrieved: 2026-09-16T10:41:06Z	source checked automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.diagram.title` Source artifact SHA-256: `0b0a225fa6f5f3ba41dffc7b320c91f47738301cf45835260eecaa03b704a097` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1) Version: version of record Retrieved: 2026-09-16T10:41:06Z	source checked automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.facts.0.value` Source artifact SHA-256: `0b0a225fa6f5f3ba41dffc7b320c91f47738301cf45835260eecaa03b704a097` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ 2 Method/2.2 Learning unit (paragraph 1); 2 Method (paragraph 1) Version: version of record Retrieved: 2026-09-16T10:41:06Z	source checked automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.facts.1.value` Source artifact SHA-256: `0b0a225fa6f5f3ba41dffc7b320c91f47738301cf45835260eecaa03b704a097` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ README.md; checkpoint/access documentation and licence scope Version: 5c5f89dcaec5098372ad1fe82d4215186fe417c1 Retrieved: 2026-09-16T19:54:20.219994+00:00	unreported automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.facts.10.value` Source artifact SHA-256: `07d86adec2ed17ed488c5af3d6348e9da967c6b6804d57093f2a8576abf132ed` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Biological inputs DNA/RNA sequence-derived physicochemical feature vectors Individual claims	PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification Original source ↗ 2 Method/2.1 Feature extraction method (paragraph 1); 4. Discussion (paragraph 3) Version: version of record Retrieved: 2026-09-16T10:41:06Z	source checked automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.facts.2.value` Source artifact SHA-256: `0b0a225fa6f5f3ba41dffc7b320c91f47738301cf45835260eecaa03b704a097` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Outputs Taxonomic class labels Individual claims	PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification Original source ↗ 3 Results/3.1 Datasets (paragraph 1); 2 Method (paragraph 1) Version: version of record Retrieved: 2026-09-16T10:41:06Z	source checked automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.facts.3.value` Source artifact SHA-256: `0b0a225fa6f5f3ba41dffc7b320c91f47738301cf45835260eecaa03b704a097` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ 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 Retrieved: 2026-09-16T19:54:20.219994+00:00	unreported automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.facts.4.value` Source artifact SHA-256: `07d86adec2ed17ed488c5af3d6348e9da967c6b6804d57093f2a8576abf132ed` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ 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 Retrieved: 2026-09-16T10:41:06Z	unreported automated source review · 2026-09-16 Audit 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. Field: `attributes.profile.facts.4.value` Source artifact SHA-256: `0b0a225fa6f5f3ba41dffc7b320c91f47738301cf45835260eecaa03b704a097` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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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

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

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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.

Related records

model: PC-mer + LR: metagenomic genus classification

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