scope_note: regulatory-variant-20261009-protocol-tang2025-cagi5-hepg2
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 |
|---|---|---|
| attributes.field scope_note Context-only references | Evaluating the representational power of pre-trained DNA language models for regulatory genomics Results 'Task 3: zero-shot variant effect prediction with MPRA data' paragraph 2 Version: Genome Biology 26:203, published 2025-07-14; PMC12261763 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 |
| attributes.source_locator Results 'Task 3: zero-shot variant effect prediction with MPRA data' paragraph 2 Context-only references | Evaluating the representational power of pre-trained DNA language models for regulatory genomics Results 'Task 3: zero-shot variant effect prediction with MPRA data' paragraph 2 Version: Genome Biology 26:203, published 2025-07-14; PMC12261763 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 |
| attributes.value gLMs fine-tuned on the lentiMPRA data also yielded improved performance (Additional file 1: Table S3); those values are not in Table 1. Context-only references | Evaluating the representational power of pre-trained DNA language models for regulatory genomics Results 'Task 3: zero-shot variant effect prediction with MPRA data' paragraph 2 Version: Genome Biology 26:203, published 2025-07-14; PMC12261763 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 | Evaluating the representational power of pre-trained DNA language models for regulatory genomics Results 'Task 3: zero-shot variant effect prediction with MPRA data' paragraph 2 Version: Genome Biology 26:203, published 2025-07-14; PMC12261763 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 regulatory-variant-20261009-protocol-tang2025-cagi5-hepg2 Context-only references | Evaluating the representational power of pre-trained DNA language models for regulatory genomics Results 'Task 3: zero-shot variant effect prediction with MPRA data' paragraph 2 Version: Genome Biology 26:203, published 2025-07-14; PMC12261763 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 scope_note: regulatory-variant-20261009-protocol-tang2025-cagi5-hepg2 Context-only references | Evaluating the representational power of pre-trained DNA language models for regulatory genomics Results 'Task 3: zero-shot variant effect prediction with MPRA data' paragraph 2 Version: Genome Biology 26:203, published 2025-07-14; PMC12261763 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 2026-10-10-6e93f504adfc · Record review: source checked
1 source records and release history
- Evaluating the representational power of pre-trained DNA language models for regulatory genomics · Original source · Genome Biology 26:203, published 2025-07-14; PMC12261763 full-text XML
Technical metadata and extraction receipts
Stable ID: regulatory-variant-20261009-claim-tang2025-finetuned-not-in-table
- field
- scope_note
- value
- gLMs fine-tuned on the lentiMPRA data also yielded improved performance (Additional file 1: Table S3); those values are not in Table 1.
- source locator
- Results 'Task 3: zero-shot variant effect prediction with MPRA data' paragraph 2
- review
- method: source-hash-verification; ai-assisted-source-review; method note: Re-downloaded the article XML, matched its SHA-256 and read the cited paragraphs with the reviewer's own JATS text extractor.; reviewer: claude; reviewer note: Separate Claude review agent, independent of the extractor; no human review claimed; date: 2026-10-09; artifact sha256: f6925cc2d93d0694ccc689970207c2df9b7b0d2562d276ede99f0c78d413b08b; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC12261763/fullTextXML; note: Hand transcription from the article text. Pending independent review. Independent review 2026-10-09: Statement matches the cited paragraph.