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benchmark · task

gene fusion breakpoint classification

This paper-specific evaluation tests gene fusion breakpoint classification using gene fusion breakpoint DNA sequences.

1 evaluations · 1 metric rows

At a glance

Explanatory profile: limited source coverage · Automated source review, 2026-09-16. This does not change the review status of its results.

Data, procedure and scoring
PropertyDescription and evidence
Record typePaper-specific task; protocol incompletely extractedBenchmarking genomic foundation models for binary classification of gene fusion breakpoints from DNA sequences · Table 2, NT / NN (middle) row, ROC AUC column
Inputsgene fusion breakpoint DNA sequencesBenchmarking genomic foundation models for binary classification of gene fusion breakpoints from DNA sequences · Table 2, NT / NN (middle) row, ROC AUC column
AssessmentROC AUCBenchmarking genomic foundation models for binary classification of gene fusion breakpoints from DNA sequences · Table 2, NT / NN (middle) row, ROC AUC column
Recorded split or evaluation settingfull test setBenchmarking genomic foundation models for binary classification of gene fusion breakpoints from DNA sequences · Table 2, NT / NN (middle) row, ROC AUC column
DatasetsNot extracted or verified for this record.
OrganismsNot extracted or verified for this record.
AssaysNot extracted or verified for this record.
AdaptationNot extracted or verified for this record.
BaselinesNot extracted or verified for this record.

How it works

Reported evaluation outline

Outline of the existing paper extraction. Split membership, fitting details and scorer implementation remain incompletely reviewed.

Reported evaluation outlinegene fusion breakpoint DNA sequences. Then: Recorded fitting or scoring procedure. Then: Assess ROC AUCgene fusion breakpoint DNAsequencesRecorded fitting or scoringprocedureAssess ROC AUC
Read the diagram as text
  1. gene fusion breakpoint DNA sequences
  2. Recorded fitting or scoring procedure
  3. Assess ROC AUC
Benchmarking genomic foundation models for binary classification of gene fusion breakpoints from DNA sequences · Table 2, NT / NN (middle) row, ROC AUC column

Evaluation context

The existing paper extraction describes: middle embedding with neural-network classifier. This description is retained with the exact evaluation records; it is not a new protocol reconstruction.

Benchmarking genomic foundation models for binary classification of gene fusion breakpoints from DNA sequences · Table 2, NT / NN (middle) row, ROC AUC column

Tested models and 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
Nucleotide Transformer + NN (middle): gene fusion breakpoint classification

middle embedding with neural-network classifier

Independent external evaluation · Evaluation metadata: needs review

0.994 ROC AUC

Unit: fraction · Direction: unknown

Uncertainty: not reported in legacy extract

Scored: Not reported · Eligible: Not reported

source checkedBenchmarking genomic foundation models for binary classification of gene fusion breakpoints from DNA sequences · Table 2, NT / NN (middle) row, ROC AUC column

Source checking is not independent reproduction.

Strengths and limitations

Profile review details

Catalogue extraction inspected; protocol claims remain limited to the cited evidence. Missing details are not presumed absent from the original paper.

Stable record: reported-task-ee34721cf55590

Sources and history

Release 2026-09-16-d74d282221a9 · Record review: needs review

Download this release
Technical metadata and extraction receipts

Stable ID: reported-task-ee34721cf55590

areas
dna-genomes
tasks
gene fusion breakpoint classification
entity level
task
version
Not reported
task
gene fusion breakpoint classification
scope note
Paper-specific evaluation task; protocol completeness requires further extraction.
missing metadata
protocol version: not_reported_in_legacy_extract
Related records

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