Seurat reference mapping (SCTransform) on Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), Accuracy
Open Problems label projection evaluation of Seurat reference mapping (SCTransform) on Label projection on Pancreas (by batch), Accuracy, scored with Accuracy.
Methods and reproduction
Open Problems label projection evaluation of Seurat reference mapping (SCTransform) on Label projection on Pancreas (by batch), Accuracy, scored with Accuracy.
- task
- Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), Accuracy
- configuration
- Seurat reference mapping (SCTransform)
- dataset subset
- Pancreas (by batch) (Open Problems label projection 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
Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).
- Configuration
- Seurat reference mapping (SCTransform)
- Task
- Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), Accuracy
- Dataset subset
- Pancreas (by batch) (Open Problems label projection split)
- origin
- Author-reported evaluation
- configuration
- Not reported
- protocol id
- open-problems-task-pancreas-batch-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 |
|---|---|---|
| Seurat reference mapping (SCTransform) on Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), Accuracy Configuration: Seurat reference mapping (SCTransform)Task: Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), AccuracyDataset subset: Pancreas (by batch) (Open Problems label projection split) Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.9588855829050582 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(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 | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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 open-problems-task-pancreas-batch-accuracy Context-only references | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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 | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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 Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Context-only references | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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 results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Context-only references | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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 Open Problems label projection evaluation of Seurat reference mapping (SCTransform) on Label projection on Pancreas (by batch), Accuracy, scored with Accuracy. Context-only references | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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 open-problems-task-pancreas-batch-accuracy Context-only references | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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 open-problems-dataset-pancreas-by-batch Context-only references | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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 open-problems-method-seurat-reference-mapping-sctransform Context-only references | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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 Seurat reference mapping (SCTransform) on Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), Accuracy Context-only references | openproblems-label primary benchmark evidence results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Version: v1.0.0 | 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
Download this releaseTechnical metadata and extraction receipts
Stable ID: open-problems-evaluation-seurat-reference-mapping-sctransform-pancreas-batch-accuracy
- areas
- cells-tissues
- tasks
- Label projection on Pancreas (by batch), Accuracy
- origin
- author_reported
- protocol
- Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).
- comparison
- protocol id: open-problems-task-pancreas-batch-accuracy; metric implementation: Accuracy
- missing metadata
- checkpoint revision: unreported; seeds: unreported; budget: unreported; split manifest: unextracted
- source locator
- results, dataset(pancreas_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy)
Related records
- benchmark: Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), Accuracy
- model: Seurat reference mapping (SCTransform)
- dataset: Pancreas (by batch) (Open Problems label projection split)
- evaluation: Seurat reference mapping (SCTransform) · Open Problems label projection PANCREAS-BATCH-ACCURACY · Accuracy