Multilayer perceptron (log scran) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Open Problems label projection evaluation of Multilayer perceptron (log scran) on Label projection on Tabula Muris Senis Lung (random split), Accuracy, scored with Accuracy.
Methods and reproduction
Open Problems label projection evaluation of Multilayer perceptron (log scran) on Label projection on Tabula Muris Senis Lung (random split), Accuracy, scored with Accuracy.
- task
- Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
- configuration
- Multilayer perceptron (log scran)
- dataset subset
- Tabula Muris Senis Lung (random split) (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
All lung cells from Tabula Muris Senis, a 500k cell-atlas from 18 organs and tissues across the mouse lifespan. Split into train/test randomly. Dimensions: 24540 cells, 17985 genes. 39 cell types (avg. 629±999 cells per cell type).
- Configuration
- Multilayer perceptron (log scran)
- Task
- Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
- Dataset subset
- Tabula Muris Senis Lung (random split) (Open Problems label projection split)
- origin
- Author-reported evaluation
- configuration
- Not reported
- protocol id
- open-problems-task-tabula-muris-senis-lung-random-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 |
|---|---|---|
| Multilayer perceptron (log scran) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy Configuration: Multilayer perceptron (log scran)Task: Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), AccuracyDataset subset: Tabula Muris Senis Lung (random split) (Open Problems label projection split) All lung cells from Tabula Muris Senis, a 500k cell-atlas from 18 organs and tissues across the mouse lifespan. Split into train/test randomly. Dimensions: 24540 cells, 17985 genes. 39 cell types (avg. 629±999 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.9285857572718155 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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-tabula-muris-senis-lung-random-accuracy Context-only references | openproblems-label primary benchmark evidence results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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 All lung cells from Tabula Muris Senis, a 500k cell-atlas from 18 organs and tissues across the mouse lifespan. Split into train/test randomly. Dimensions: 24540 cells, 17985 genes. 39 cell types (avg. 629±999 cells per cell type). Context-only references | openproblems-label primary benchmark evidence results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), metric(accuracy) Context-only references | openproblems-label primary benchmark evidence results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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 Multilayer perceptron (log scran) on Label projection on Tabula Muris Senis Lung (random split), Accuracy, scored with Accuracy. Context-only references | openproblems-label primary benchmark evidence results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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-tabula-muris-senis-lung-random-accuracy Context-only references | openproblems-label primary benchmark evidence results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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-tabula-muris-senis-lung-random-split Context-only references | openproblems-label primary benchmark evidence results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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-multilayer-perceptron-log-scran Context-only references | openproblems-label primary benchmark evidence results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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 Multilayer perceptron (log scran) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy Context-only references | openproblems-label primary benchmark evidence results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), 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-multilayer-perceptron-log-scran-tabula-muris-senis-lung-random-accuracy
- areas
- cells-tissues
- tasks
- Label projection on Tabula Muris Senis Lung (random split), Accuracy
- origin
- author_reported
- protocol
- All lung cells from Tabula Muris Senis, a 500k cell-atlas from 18 organs and tissues across the mouse lifespan. Split into train/test randomly. Dimensions: 24540 cells, 17985 genes. 39 cell types (avg. 629±999 cells per cell type).
- comparison
- protocol id: open-problems-task-tabula-muris-senis-lung-random-accuracy; metric implementation: Accuracy
- missing metadata
- checkpoint revision: unreported; seeds: unreported; budget: unreported; split manifest: unextracted
- source locator
- results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), metric(accuracy)
Related records
- benchmark: Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
- model: Multilayer perceptron (log scran)
- dataset: Tabula Muris Senis Lung (random split) (Open Problems label projection split)
- evaluation: Multilayer perceptron (log scran) · Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY · Accuracy