comparison_design: dna-pathogen-20261012-bertax-benchmark
Comparison design of BERTax taxonomic classification of genome fragments (Mock et al. 2022)
All methods compared have exactly the same reference or training data as BERTax; whole reference genomes are not included, which the authors call a necessary deviation from the designed use of database methods.
Descriptive fact transcribed from the pinned source.
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.
6 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Claimed field comparison_design Context-only references | Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks Results 'Comparison to Other Classification Approaches' paragraph 1 Version: PNAS 119(35):e2122636119, published 2022-08-26; PMC9436379 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Source location Results 'Comparison to Other Classification Approaches' paragraph 1 Context-only references | Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks Results 'Comparison to Other Classification Approaches' paragraph 1 Version: PNAS 119(35):e2122636119, published 2022-08-26; PMC9436379 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Claimed value All methods compared have exactly the same reference or training data as BERTax; whole reference genomes are not included, which the authors call a necessary deviation from the designed use of database methods. Context-only references | Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks Results 'Comparison to Other Classification Approaches' paragraph 1 Version: PNAS 119(35):e2122636119, published 2022-08-26; PMC9436379 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Description Descriptive fact transcribed from the pinned source. Context-only references | Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks Results 'Comparison to Other Classification Approaches' paragraph 1 Version: PNAS 119(35):e2122636119, published 2022-08-26; PMC9436379 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Relationship: subject dna-pathogen-20261012-bertax-benchmark Context-only references | Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks Results 'Comparison to Other Classification Approaches' paragraph 1 Version: PNAS 119(35):e2122636119, published 2022-08-26; PMC9436379 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Name comparison_design: dna-pathogen-20261012-bertax-benchmark Context-only references | Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks Results 'Comparison to Other Classification Approaches' paragraph 1 Version: PNAS 119(35):e2122636119, published 2022-08-26; PMC9436379 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-10-22-1b7cf027e4f6 · Record review: source checked
1 source record and release history
- Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks · Original source · PNAS 119(35):e2122636119, published 2022-08-26; PMC9436379 full-text XML
Technical metadata and extraction receipts
Stable ID: dna-pathogen-20261012-bertax-claim-same-reference-data
- field
- comparison_design
- value
- All methods compared have exactly the same reference or training data as BERTax; whole reference genomes are not included, which the authors call a necessary deviation from the designed use of database methods.
- source locator
- Results 'Comparison to Other Classification Approaches' paragraph 1
- review
- method: source-hash-verification; independent-cell-check; reviewer: claude; reviewer note: Separate Claude review agent (rev-mlvb), independent of the extracting agent; no human review claimed; date: 2026-10-12; artifact sha256: c0bb2f1bba8680b300076292389b39346ae58bea4bdf28647dd9462333b3bcd7; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC9436379/fullTextXML; method note: Transcribed from the pinned article XML text.; note: Checked against the re-downloaded article XML (SHA-256 matches).