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result · source checked

0.965 AUC

DNABERT2-Enhancer · AUC · Liu training dataset

Tested model
DNABERT2-Enhancer
Task or benchmark
enhancer recognition
Dataset
Liu training dataset
Procedure
first-layer enhancer versus non-enhancer classifier
Evaluation
DNABERT2-Enhancer: enhancer recognition
Evidence
Author-reported evaluation · source checkedUtilizing a deep learning model based on BERT for identifying enhancers and their strength · Table 4, first-layer DNABERT2-Enhancer row, AUC column

A source-checked result verifies the numerical transcription, not every model or protocol detail. Evaluation metadata: needs review. Source checked does not mean independently reproduced.

Evaluation results

Release 2026-09-16-d74d282221a9 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.

Results grouped by the exact reported evaluation
Metric and findingCoverage and uncertaintyEvidence
DNABERT2-Enhancer: enhancer recognition

first-layer enhancer versus non-enhancer classifier

Author-reported evaluation · Evaluation metadata: needs review

0.965 AUC

Unit: fraction · Direction: unknown

Uncertainty: not reported in legacy extract

Scored: Not reported · Eligible: Not reported

source checkedUtilizing a deep learning model based on BERT for identifying enhancers and their strength · Table 4, first-layer DNABERT2-Enhancer row, AUC column

Source checking is not independent reproduction.

Sources and history

Release 2026-09-16-d74d282221a9 · Record review: source checked

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Technical metadata and extraction receipts

Stable ID: b2-dnabert2-enhancer-2025

areas
dna-genomes
tasks
enhancer recognition
printed value
0.965
numeric value
0.965
metric
AUC
metric direction
unknown
unit
fraction
uncertainty
Not reported
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.; evidence: Original PMC XML table headers, row groups and caption inspected; printed value 0.965.; artifact sha256: d052b80efe7bfc1380994ad28503a5575f04ef940f74d5c9c137cb4ba6827863; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC11981215/fullTextXML
legacy id
b2-dnabert2-enhancer-2025
legacy row
id: b2-dnabert2-enhancer-2025; paper id: dnabert2-enhancer-2025; domain id: dna-genomes; task: enhancer recognition; model: DNABERT2-Enhancer; model version: not stated in table; dataset: Liu training dataset; dataset version: Not reported; split: 5-fold cross-validation; metric: AUC; value: 0.965; unit: fraction; uncertainty: Not reported; protocol: first-layer enhancer versus non-enhancer classifier; source locator: Table 4, first-layer DNABERT2-Enhancer row, AUC column; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC11981215/; evaluation origin: author_reported; reviewed utc: 2026-09-15T23:33:26Z
missing metadata
dataset version: not_reported_in_legacy_extract; uncertainty: not_reported_in_legacy_extract
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