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Task

Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy

Label projection on Tabula Muris Senis Lung (random split), Accuracy. Scored with Accuracy on Tabula Muris Senis Lung (random 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).

16 evaluations · 16 metric rows

Overview

Label projection on Tabula Muris Senis Lung (random split), Accuracy. Scored with Accuracy on Tabula Muris Senis Lung (random 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).

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluation design

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Benchmarks

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Recorded evaluations

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Run instructions

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Published comparisons

Explore the results reported under one evaluation protocol. Each figure keeps its source, dataset and metric together; it is not a ranking across studies. The pooled view gathers every source table that reports the same metric and names what it does not hold constant.

Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy

accuracy (fraction) · Higher values are better for this metric.

Every method Open Problems label projection reports on Label projection on Tabula Muris Senis Lung (random split), Accuracy, scored with Accuracy on Tabula Muris Senis Lung (random split).

Evaluation protocol · Tabula Muris Senis Lung (random split) (Open Problems label projection split)

  1. K-neighbors classifier (log CP10k) · Configuration · Author-reported evaluation0.8611835506519558
  2. Logistic regression (log CP10k) · Configuration · Author-reported evaluation0.925777331995988
  3. True Labels · Method · Author-reported evaluation1
  4. Majority Vote · Configuration · Author-reported evaluation0.22286860581745235
  5. Random Labels · Method · Author-reported evaluation0.08926780341023069
  6. Multilayer perceptron (log CP10k) · Configuration · Author-reported evaluation0.931394182547643
  7. K-neighbors classifier (log scran) · Configuration · Author-reported evaluation0.8686058174523571
  8. XGBoost (log CP10k) · Configuration · Author-reported evaluation0.8736208625877633
  9. Logistic regression (log scran) · Configuration · Author-reported evaluation0.9251755265797392
  10. XGBoost (log scran) · Configuration · Author-reported evaluation0.8651955867602809
  11. Seurat reference mapping (SCTransform) · Configuration · Author-reported evaluation0.9119358074222668
  12. Multilayer perceptron (log scran) · Configuration · Author-reported evaluation0.9285857572718155
  13. scANVI (Seurat v3 2000 HVG) · Configuration · Author-reported evaluation0.8409227683049147
  14. scArches+scANVI (All genes) · Configuration · Author-reported evaluation0.7837512537612839
  15. scArches+scANVI (Seurat v3 2000 HVG) · Configuration · Author-reported evaluation0.7223671013039117
  16. scANVI (All genes) · Configuration · Author-reported evaluation0.8641925777331996

Source order is preserved. Plotted marks show point estimates; uncertainty, where reported, is retained in the printed values and table. Differences do not establish statistical significance.

openproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), metric(accuracy)
Values, uncertainty and evidence
accuracy: original source values
Tested entityPrinted valueUncertaintyEvidence
K-neighbors classifier (log CP10k) · Configuration0.8611835506519558 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(k_neighbors_classifier), paramset(log CP10k), metric(accuracy)
Logistic regression (log CP10k) · Configuration0.925777331995988 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(logistic_regression), paramset(log CP10k), metric(accuracy)
True Labels · Method1 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(true_labels), paramset(none), metric(accuracy)
Majority Vote · Configuration0.22286860581745235 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(majority_vote), paramset(none), metric(accuracy)
Random Labels · Method0.08926780341023069 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(random_labels), paramset(none), metric(accuracy)
Multilayer perceptron (log CP10k) · Configuration0.931394182547643 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log CP10k), metric(accuracy)
K-neighbors classifier (log scran) · Configuration0.8686058174523571 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(k_neighbors_classifier), paramset(log scran), metric(accuracy)
XGBoost (log CP10k) · Configuration0.8736208625877633 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(xgboost), paramset(log CP10k), metric(accuracy)
Logistic regression (log scran) · Configuration0.9251755265797392 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(logistic_regression), paramset(log scran), metric(accuracy)
XGBoost (log scran) · Configuration0.8651955867602809 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(xgboost), paramset(log scran), metric(accuracy)
Seurat reference mapping (SCTransform) · Configuration0.9119358074222668 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy)
Multilayer perceptron (log scran) · Configuration0.9285857572718155 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(multilayer_perceptron), paramset(log scran), metric(accuracy)
scANVI (Seurat v3 2000 HVG) · Configuration0.8409227683049147 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)
scArches+scANVI (All genes) · Configuration0.7837512537612839 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(scarches_scanvi), paramset(All genes), metric(accuracy)
scArches+scANVI (Seurat v3 2000 HVG) · Configuration0.7223671013039117 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)
scANVI (All genes) · Configuration0.8641925777331996 fractionNot reportedAuthor-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(scanvi), paramset(All genes), metric(accuracy)
Scope and limitations
  • Results published by the Open Problems project, source checked but not independently reproduced.
  • This covers the label projection task at v1.0.0 only, not the whole Open Problems suite.
  • true_labels and random_labels are controls that bound the scale, not competing methods.
  • Preprocessing is part of the run, so the same method appears once per parameter set.

Source transcription and grouping reviewed by automated source review on 2026-09-18. These experiments were not independently reproduced by rewire.

Tested entities and results

Release 2026-09-17-134cd1815de8 · 16 evaluations · 16 metric rows. 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.

Results grouped by the exact reported evaluation
Metric and findingCoverage and uncertaintyEvidence
K-neighbors classifier (log CP10k) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: K-neighbors classifier (log CP10k)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

0.8611835506519558 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(k_neighbors_classifier), paramset(log CP10k), metric(accuracy)

Source checking is not independent reproduction.

K-neighbors classifier (log scran) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: K-neighbors classifier (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

0.8686058174523571 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(k_neighbors_classifier), paramset(log scran), metric(accuracy)

Source checking is not independent reproduction.

Logistic regression (log CP10k) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: Logistic regression (log CP10k)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

0.925777331995988 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(logistic_regression), paramset(log CP10k), metric(accuracy)

Source checking is not independent reproduction.

Logistic regression (log scran) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: Logistic regression (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

0.9251755265797392 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(logistic_regression), paramset(log scran), metric(accuracy)

Source checking is not independent reproduction.

Majority Vote on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: Majority VoteTask: 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

0.22286860581745235 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(majority_vote), paramset(none), metric(accuracy)

Source checking is not independent reproduction.

Multilayer perceptron (log CP10k) 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 CP10k)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

0.931394182547643 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 CP10k), metric(accuracy)

Source checking is not independent reproduction.

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.

Random Labels on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Method: Random LabelsTask: 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

0.08926780341023069 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(random_labels), paramset(none), metric(accuracy)

Source checking is not independent reproduction.

scANVI (All genes) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: scANVI (All genes)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

0.8641925777331996 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(scanvi), paramset(All genes), metric(accuracy)

Source checking is not independent reproduction.

scANVI (Seurat v3 2000 HVG) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: scANVI (Seurat v3 2000 HVG)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

0.8409227683049147 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(scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (All genes) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: scArches+scANVI (All genes)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

0.7837512537612839 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(scarches_scanvi), paramset(All genes), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: scArches+scANVI (Seurat v3 2000 HVG)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

0.7223671013039117 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(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

Seurat reference mapping (SCTransform) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: Seurat reference mapping (SCTransform)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

0.9119358074222668 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(seurat_reference_mapping), paramset(SCTransform), metric(accuracy)

Source checking is not independent reproduction.

True Labels on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Method: True LabelsTask: 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

1 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(true_labels), paramset(none), metric(accuracy)

Source checking is not independent reproduction.

XGBoost (log CP10k) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: XGBoost (log CP10k)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

0.8736208625877633 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(xgboost), paramset(log CP10k), metric(accuracy)

Source checking is not independent reproduction.

XGBoost (log scran) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy
Configuration: XGBoost (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

0.8651955867602809 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(xgboost), 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.

1 evidence row matching the loaded filters

Claims, original sources and review scope · Release 2026-09-17-134cd1815de8
Property and statementOriginal source and locationReview and provenance
Relationship: part of

discovery-benchmark-open-problems

Individual claims		openproblems-label primary benchmark evidence

Original source ↗

results, dataset(tabula_muris_senis_lung_random), metric(accuracy)

Version: v1.0.0
Retrieved: 2026-09-16T21:16:30.026457+00:00

source checked

automated source review · 2026-09-18

Audit details

Primary-source transcription with no human sign-off and no independent reproduction.

Field: links:part_of:discovery-benchmark-open-problems

Claim: open-problems-association-tabula-muris-senis-lung-random-accuracy

Source artifact SHA-256: e223ab712ff55997a3abe659f280d4ea2952700e767b87e02c434701da9833c1

Hash scope: Exact retrieved primary paper artifact bytes.

Inspected artifact

All evidence (CSV)All evidence (JSONL)How to read the evidence

Sources and history

Release 2026-09-17-134cd1815de8 · Record review: source checked

1 source records and release historyDownload this release
Technical metadata and extraction receipts

Stable ID: open-problems-task-tabula-muris-senis-lung-random-accuracy

areas
cells-tissues
tasks
Label projection on Tabula Muris Senis Lung (random split), Accuracy
metric
Accuracy
metric direction
higher
dataset
Tabula Muris Senis Lung (random split)
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).
source locator
results, dataset(tabula_muris_senis_lung_random), metric(accuracy)
comparison panels
id: open-problems-panel-tabula-muris-senis-lung-random-accuracy; title: Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy; protocol id: open-problems-task-tabula-muris-senis-lung-random-accuracy; dataset id: open-problems-dataset-tabula-muris-senis-lung-random-split; metric: accuracy; unit: fraction; direction: higher; result ids: open-problems-result-k-neighbors-classifier-log-cp10k-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-logistic-regression-log-cp10k-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-true-labels-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-majority-vote-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-random-labels-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-multilayer-perceptron-log-cp10k-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-k-neighbors-classifier-log-scran-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-xgboost-log-cp10k-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-logistic-regression-log-scran-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-xgboost-log-scran-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-seurat-reference-mapping-sctransform-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-multilayer-perceptron-log-scran-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-scanvi-seurat-v3-2000-hvg-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-scarches-plus-scanvi-all-genes-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-scarches-plus-scanvi-seurat-v3-2000-hvg-tabula-muris-senis-lung-random-accuracy-accuracy; open-problems-result-scanvi-all-genes-tabula-muris-senis-lung-random-accuracy-accuracy; source ids: expansion-p3-open-problems; source locator: results, dataset(tabula_muris_senis_lung_random), metric(accuracy); context: Every method Open Problems label projection reports on Label projection on Tabula Muris Senis Lung (random split), Accuracy, scored with Accuracy on Tabula Muris Senis Lung (random split).; caveats: Results published by the Open Problems project, source checked but not independently reproduced.; This covers the label projection task at v1.0.0 only, not the whole Open Problems suite.; true_labels and random_labels are controls that bound the scale, not competing methods.; Preprocessing is part of the run, so the same method appears once per parameter set.; review: method: automated_source_review; date: 2026-09-18
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