Reported AUC for DNABERT2-Enhancer
Evidence
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Evidence table
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6 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.field attributes.printed_value Context-only references | Utilizing a deep learning model based on BERT for identifying enhancers and their strength Table 4, first-layer DNABERT2-Enhancer row, AUC column Version: journal full text in PMC | 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 Table 4, first-layer DNABERT2-Enhancer row, AUC column Context-only references | Utilizing a deep learning model based on BERT for identifying enhancers and their strength Table 4, first-layer DNABERT2-Enhancer row, AUC column Version: journal full text in PMC | 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 0.965 Context-only references | Utilizing a deep learning model based on BERT for identifying enhancers and their strength Table 4, first-layer DNABERT2-Enhancer row, AUC column Version: journal full text in PMC | 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 No value recorded Context-only references | Utilizing a deep learning model based on BERT for identifying enhancers and their strength Table 4, first-layer DNABERT2-Enhancer row, AUC column Version: journal full text in PMC | missing or unspecified No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Relationship: subject b2-dnabert2-enhancer-2025 Context-only references | Utilizing a deep learning model based on BERT for identifying enhancers and their strength Table 4, first-layer DNABERT2-Enhancer row, AUC column Version: journal full text in PMC | 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 Reported AUC for DNABERT2-Enhancer Context-only references | Utilizing a deep learning model based on BERT for identifying enhancers and their strength Table 4, first-layer DNABERT2-Enhancer row, AUC column Version: journal full text in PMC | 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
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Release 2026-09-29-06401fd5b220 · Record review: source checked
1 source records and release history
- Utilizing a deep learning model based on BERT for identifying enhancers and their strength · Original source · journal full text in PMC
Technical metadata and extraction receipts
Stable ID: claim-b2-dnabert2-enhancer-2025
- areas
- dna-genomes
- tasks
- enhancer recognition
- field
- attributes.printed_value
- value
- 0.965
- source locator
- Table 4, first-layer DNABERT2-Enhancer row, AUC column
- review
- method: independent_ai_table_review; reviewer: Codex secondary table review; reviewed at: 2026-09-16T10:38:57.558204+00:00; notes: Resolved the first-layer row group. DNABERT2-Enhancer AUC is 0.965, whereas second-layer AUC is 0.933. The caption explicitly describes 5-fold cross-validation on Liu training data, not an independent held-out test.