Baseline CNN (PyTorch) on Genomic Benchmarks HUMAN-OCR-ENSEMBL-ACCURACY: human_ocr_ensembl, Accuracy
Genomic Benchmarks evaluation of Baseline CNN (PyTorch) on human_ocr_ensembl, Accuracy, scored with Accuracy.
Methods and reproduction
Genomic Benchmarks evaluation of Baseline CNN (PyTorch) on human_ocr_ensembl, Accuracy, scored with Accuracy.
- task
- Genomic Benchmarks HUMAN-OCR-ENSEMBL-ACCURACY: human_ocr_ensembl, Accuracy
- configuration
- Baseline CNN (PyTorch)
- dataset subset
- human_ocr_ensembl (Genomic Benchmarks split)
- Split
- Not reported
- Adaptation
- Not reported
- Scoring implementation
- Accuracy
No execution recipe has been verified for this exact configuration and evaluation. A benchmark's general instructions may use different inputs, splits or model settings.
Reproducing this published result requires matching its model configuration, data, split and scorer. Source checking or a successful smoke test does not establish score reproduction.
Evaluation procedure
The paper's own three-layer convolutional baseline, trained on each dataset's training split and scored on its test split. Architecture is in Table 1.
- Configuration
- Baseline CNN (PyTorch)
- Task
- Genomic Benchmarks HUMAN-OCR-ENSEMBL-ACCURACY: human_ocr_ensembl, Accuracy
- Dataset subset
- human_ocr_ensembl (Genomic Benchmarks split)
- origin
- Author-reported evaluation
- configuration
- Not reported
- protocol id
- genomic-benchmarks-task-human-ocr-ensembl-accuracy
- metric implementation
- Accuracy
Metadata review: source checked. Unreported conditions prevent automatic comparisons.
Evaluation results
Release 2026-09-17-134cd1815de8 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard. Where several source tables report the same metric, the published comparisons above offer a pooled view that names what it does not hold constant.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| Baseline CNN (PyTorch) on Genomic Benchmarks HUMAN-OCR-ENSEMBL-ACCURACY: human_ocr_ensembl, Accuracy Configuration: Baseline CNN (PyTorch)Task: Genomic Benchmarks HUMAN-OCR-ENSEMBL-ACCURACY: human_ocr_ensembl, AccuracyDataset subset: human_ocr_ensembl (Genomic Benchmarks split) The paper's own three-layer convolutional baseline, trained on each dataset's training split and scored on its test split. Architecture is in Table 1. Author-reported evaluation · Evaluation metadata: source checked | ||
| 68.0% accuracy Unit: percent · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedGenomic benchmarks: a collection of datasets for genomic sequence classification · Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Source checking is not 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.
10 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.comparison.metric_implementation Accuracy Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| attributes.comparison.protocol_id genomic-benchmarks-task-human-ocr-ensembl-accuracy Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| attributes.origin author_reported Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| attributes.protocol The paper's own three-layer convolutional baseline, trained on each dataset's training split and scored on its test split. Architecture is in Table 1. Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| attributes.source_locator Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| description Genomic Benchmarks evaluation of Baseline CNN (PyTorch) on human_ocr_ensembl, Accuracy, scored with Accuracy. Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Relationship: benchmark genomic-benchmarks-task-human-ocr-ensembl-accuracy Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Relationship: dataset genomic-benchmarks-dataset-human-ocr-ensembl Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Relationship: model genomic-benchmarks-method-baseline-cnn-pytorch Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| name Baseline CNN (PyTorch) on Genomic Benchmarks HUMAN-OCR-ENSEMBL-ACCURACY: human_ocr_ensembl, Accuracy Context-only references | Genomic benchmarks: a collection of datasets for genomic sequence classification Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy) Version: PMC10150520 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
Sources and history
Release 2026-09-17-134cd1815de8 · Record review: source checked
1 source records and release history
- Genomic benchmarks: a collection of datasets for genomic sequence classification · Original source · PMC10150520
Technical metadata and extraction receipts
Stable ID: genomic-benchmarks-evaluation-baseline-cnn-pytorch-human-ocr-ensembl-accuracy
- areas
- dna-genomes
- tasks
- human_ocr_ensembl, Accuracy
- origin
- author_reported
- protocol
- The paper's own three-layer convolutional baseline, trained on each dataset's training split and scored on its test split. Architecture is in Table 1.
- comparison
- protocol id: genomic-benchmarks-task-human-ocr-ensembl-accuracy; metric implementation: Accuracy
- missing metadata
- checkpoint revision: unreported; seeds: unreported; budget: unreported; split manifest: unextracted
- source locator
- Table 2, row(human_ocr_ensembl), column(Baseline CNN (PyTorch) Accuracy)