Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
Label projection on CeNGEN (split by batch), Accuracy. Scored with Accuracy on CeNGEN (split by batch). 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type).
Overview
Label projection on CeNGEN (split by batch), Accuracy. Scored with Accuracy on CeNGEN (split by batch). 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type).
Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.
Evaluation design
Benchmarks bring together tasks and protocols. A task describes the biological question; a protocol defines a particular test.
Benchmarks
These source-backed links do not make different protocols or scores interchangeable.
Recorded evaluations
Each evaluation records what was tested and under which conditions.
- K-neighbors classifier (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- K-neighbors classifier (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- Logistic regression (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- Logistic regression (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- Majority Vote on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- Multilayer perceptron (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- Multilayer perceptron (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- Random Labels on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- scANVI (All genes) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- scArches+scANVI (All genes) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
Run instructions
No runnable recipe has been reviewed for this task. Dataset access, model requirements, licences and compute requirements must be checked against its sources before execution.
A task describes a biological question. Choose a linked protocol to obtain concrete split and scoring instructions.
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 CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
accuracy (fraction) · Higher values are better for this metric.
Every method Open Problems label projection reports on Label projection on CeNGEN (split by batch), Accuracy, scored with Accuracy on CeNGEN (split by batch).
Evaluation protocol · CeNGEN (split by batch) (Open Problems label projection split)
- True Labels · Method · Author-reported evaluation1
- Majority Vote · Configuration · Author-reported evaluation0.022168963451168363
- Random Labels · Method · Author-reported evaluation0.014379868184541641
- K-neighbors classifier (log CP10k) · Configuration · Author-reported evaluation0.8124625524266027
- Logistic regression (log CP10k) · Configuration · Author-reported evaluation0.8783702816057519
- Multilayer perceptron (log CP10k) · Configuration · Author-reported evaluation0.8250449370880767
- K-neighbors classifier (log scran) · Configuration · Author-reported evaluation0.7872977831036548
- Logistic regression (log scran) · Configuration · Author-reported evaluation0.7723187537447573
- Multilayer perceptron (log scran) · Configuration · Author-reported evaluation0.8568004793289394
- Seurat reference mapping (SCTransform) · Configuration · Author-reported evaluation0.8478130617136009
- XGBoost (log CP10k) · Configuration · Author-reported evaluation0.8274415817855003
- XGBoost (log scran) · Configuration · Author-reported evaluation0.8304373876572798
- scANVI (Seurat v3 2000 HVG) · Configuration · Author-reported evaluation0.26243259436788496
- scArches+scANVI (Seurat v3 2000 HVG) · Configuration · Author-reported evaluation0.08028759736369083
- scArches+scANVI (All genes) · Configuration · Author-reported evaluation0.24565608148591972
- scANVI (All genes) · Configuration · Author-reported evaluation0.6470940683043739
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(cengen_batch), metric(accuracy)Values, uncertainty and evidence
| Tested entity | Printed value | Uncertainty | Evidence |
|---|---|---|---|
| True Labels · Method | 1 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(true_labels), paramset(none), metric(accuracy) |
| Majority Vote · Configuration | 0.022168963451168363 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(majority_vote), paramset(none), metric(accuracy) |
| Random Labels · Method | 0.014379868184541641 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(random_labels), paramset(none), metric(accuracy) |
| K-neighbors classifier (log CP10k) · Configuration | 0.8124625524266027 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(k_neighbors_classifier), paramset(log CP10k), metric(accuracy) |
| Logistic regression (log CP10k) · Configuration | 0.8783702816057519 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(logistic_regression), paramset(log CP10k), metric(accuracy) |
| Multilayer perceptron (log CP10k) · Configuration | 0.8250449370880767 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(multilayer_perceptron), paramset(log CP10k), metric(accuracy) |
| K-neighbors classifier (log scran) · Configuration | 0.7872977831036548 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(k_neighbors_classifier), paramset(log scran), metric(accuracy) |
| Logistic regression (log scran) · Configuration | 0.7723187537447573 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(logistic_regression), paramset(log scran), metric(accuracy) |
| Multilayer perceptron (log scran) · Configuration | 0.8568004793289394 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(multilayer_perceptron), paramset(log scran), metric(accuracy) |
| Seurat reference mapping (SCTransform) · Configuration | 0.8478130617136009 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) |
| XGBoost (log CP10k) · Configuration | 0.8274415817855003 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(xgboost), paramset(log CP10k), metric(accuracy) |
| XGBoost (log scran) · Configuration | 0.8304373876572798 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(xgboost), paramset(log scran), metric(accuracy) |
| scANVI (Seurat v3 2000 HVG) · Configuration | 0.26243259436788496 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy) |
| scArches+scANVI (Seurat v3 2000 HVG) · Configuration | 0.08028759736369083 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy) |
| scArches+scANVI (All genes) · Configuration | 0.24565608148591972 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(scarches_scanvi), paramset(All genes), metric(accuracy) |
| scANVI (All genes) · Configuration | 0.6470940683043739 fraction | Not reported | Author-reported evaluation · source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), 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.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| K-neighbors classifier (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: K-neighbors classifier (log CP10k)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8124625524266027 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), 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 CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: K-neighbors classifier (log scran)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.7872977831036548 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(k_neighbors_classifier), paramset(log scran), metric(accuracy) Source checking is not independent reproduction. |
| Logistic regression (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: Logistic regression (log CP10k)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8783702816057519 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(logistic_regression), paramset(log CP10k), metric(accuracy) Source checking is not independent reproduction. |
| Logistic regression (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: Logistic regression (log scran)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.7723187537447573 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(logistic_regression), paramset(log scran), metric(accuracy) Source checking is not independent reproduction. |
| Majority Vote on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: Majority VoteTask: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.022168963451168363 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(majority_vote), paramset(none), metric(accuracy) Source checking is not independent reproduction. |
| Multilayer perceptron (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: Multilayer perceptron (log CP10k)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8250449370880767 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(multilayer_perceptron), paramset(log CP10k), metric(accuracy) Source checking is not independent reproduction. |
| Multilayer perceptron (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: Multilayer perceptron (log scran)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8568004793289394 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(multilayer_perceptron), paramset(log scran), metric(accuracy) Source checking is not independent reproduction. |
| Random Labels on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Method: Random LabelsTask: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.014379868184541641 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(random_labels), paramset(none), metric(accuracy) Source checking is not independent reproduction. |
| scANVI (All genes) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: scANVI (All genes)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.6470940683043739 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(scanvi), paramset(All genes), metric(accuracy) Source checking is not independent reproduction. |
| scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: scANVI (Seurat v3 2000 HVG)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.26243259436788496 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy) Source checking is not independent reproduction. |
| scArches+scANVI (All genes) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: scArches+scANVI (All genes)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.24565608148591972 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), 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 CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: scArches+scANVI (Seurat v3 2000 HVG)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.08028759736369083 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), 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 CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: Seurat reference mapping (SCTransform)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8478130617136009 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(seurat_reference_mapping), paramset(SCTransform), metric(accuracy) Source checking is not independent reproduction. |
| True Labels on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Method: True LabelsTask: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 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(cengen_batch), method(true_labels), paramset(none), metric(accuracy) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: XGBoost (log CP10k)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8274415817855003 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(xgboost), paramset(log CP10k), metric(accuracy) Source checking is not independent reproduction. |
| XGBoost (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy Configuration: XGBoost (log scran)Task: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), AccuracyDataset subset: CeNGEN (split by batch) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8304373876572798 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), 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
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Relationship: part of discovery-benchmark-open-problems Individual claims | openproblems-label primary benchmark evidence results, dataset(cengen_batch), metric(accuracy) Version: v1.0.0 | source checked automated source review · 2026-09-18 Audit detailsPrimary-source transcription with no human sign-off and no independent reproduction. Field: Claim: open-problems-association-cengen-batch-accuracy 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-task-cengen-batch-accuracy
- areas
- cells-tissues
- tasks
- Label projection on CeNGEN (split by batch), Accuracy
- metric
- Accuracy
- metric direction
- higher
- dataset
- CeNGEN (split by batch)
- protocol
- 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type).
- source locator
- results, dataset(cengen_batch), metric(accuracy)
- comparison panels
- id: open-problems-panel-cengen-batch-accuracy; title: Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy; protocol id: open-problems-task-cengen-batch-accuracy; dataset id: open-problems-dataset-cengen-split-by-batch; metric: accuracy; unit: fraction; direction: higher; result ids: open-problems-result-true-labels-cengen-batch-accuracy-accuracy; open-problems-result-majority-vote-cengen-batch-accuracy-accuracy; open-problems-result-random-labels-cengen-batch-accuracy-accuracy; open-problems-result-k-neighbors-classifier-log-cp10k-cengen-batch-accuracy-accuracy; open-problems-result-logistic-regression-log-cp10k-cengen-batch-accuracy-accuracy; open-problems-result-multilayer-perceptron-log-cp10k-cengen-batch-accuracy-accuracy; open-problems-result-k-neighbors-classifier-log-scran-cengen-batch-accuracy-accuracy; open-problems-result-logistic-regression-log-scran-cengen-batch-accuracy-accuracy; open-problems-result-multilayer-perceptron-log-scran-cengen-batch-accuracy-accuracy; open-problems-result-seurat-reference-mapping-sctransform-cengen-batch-accuracy-accuracy; open-problems-result-xgboost-log-cp10k-cengen-batch-accuracy-accuracy; open-problems-result-xgboost-log-scran-cengen-batch-accuracy-accuracy; open-problems-result-scanvi-seurat-v3-2000-hvg-cengen-batch-accuracy-accuracy; open-problems-result-scarches-plus-scanvi-seurat-v3-2000-hvg-cengen-batch-accuracy-accuracy; open-problems-result-scarches-plus-scanvi-all-genes-cengen-batch-accuracy-accuracy; open-problems-result-scanvi-all-genes-cengen-batch-accuracy-accuracy; source ids: expansion-p3-open-problems; source locator: results, dataset(cengen_batch), metric(accuracy); context: Every method Open Problems label projection reports on Label projection on CeNGEN (split by batch), Accuracy, scored with Accuracy on CeNGEN (split by batch).; 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
Related records
- part of: Open Problems
- subject: Open Problems label projection CENGEN-BATCH-ACCURACY: part of discovery-benchmark-open-problems
- benchmark: K-neighbors classifier (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: K-neighbors classifier (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: Logistic regression (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: Logistic regression (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: Majority Vote on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: Multilayer perceptron (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: Multilayer perceptron (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: Random Labels on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: scANVI (All genes) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: scArches+scANVI (All genes) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: Seurat reference mapping (SCTransform) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: True Labels on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: XGBoost (log CP10k) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy
- benchmark: XGBoost (log scran) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy