The split of Pancreas (random split) that Open Problems label projection evaluated on. The upstream dataset release is not catalogued here, so no claim is made that this matches its original splits.
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48 evaluations · 48 results. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: K-neighbors classifier (log CP10k) | Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.965 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(k_neighbors_classifier), paramset(log CP10k), metric(accuracy) |
| Configuration: K-neighbors classifier (log CP10k) | Task: Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.964 f1 fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(k_neighbors_classifier), paramset(log CP10k), metric(f1) |
| Configuration: K-neighbors classifier (log CP10k) | Task: Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.896 f1-macro fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(k_neighbors_classifier), paramset(log CP10k), metric(f1_macro) |
| Configuration: K-neighbors classifier (log scran) | Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.964 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(k_neighbors_classifier), paramset(log scran), metric(accuracy) |
| Configuration: K-neighbors classifier (log scran) | Task: Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.964 f1 fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(k_neighbors_classifier), paramset(log scran), metric(f1) |
| Configuration: K-neighbors classifier (log scran) | Task: Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.772 f1-macro fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(k_neighbors_classifier), paramset(log scran), metric(f1_macro) |
| Configuration: Logistic regression (log CP10k) | Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.988 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(logistic_regression), paramset(log CP10k), metric(accuracy) |
| Configuration: Logistic regression (log CP10k) | Task: Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.988 f1 fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(logistic_regression), paramset(log CP10k), metric(f1) |
| Configuration: Logistic regression (log CP10k) | Task: Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.972 f1-macro fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(logistic_regression), paramset(log CP10k), metric(f1_macro) |
| Configuration: Logistic regression (log scran) | Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.945 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(logistic_regression), paramset(log scran), metric(accuracy) |
| Configuration: Logistic regression (log scran) | Task: Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.938 f1 fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(logistic_regression), paramset(log scran), metric(f1) |
| Configuration: Logistic regression (log scran) | Task: Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.632 f1-macro fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(logistic_regression), paramset(log scran), metric(f1_macro) |
| Configuration: Majority Vote | Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.329 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(majority_vote), paramset(none), metric(accuracy) |
| Configuration: Majority Vote | Task: Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.163 f1 fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(majority_vote), paramset(none), metric(f1) |
| Configuration: Majority Vote | Task: Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.0354 f1-macro fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(majority_vote), paramset(none), metric(f1_macro) |
| Configuration: Multilayer perceptron (log CP10k) | Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.988 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(multilayer_perceptron), paramset(log CP10k), metric(accuracy) |
| Configuration: Multilayer perceptron (log CP10k) | Task: Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.988 f1 fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(multilayer_perceptron), paramset(log CP10k), metric(f1) |
| Configuration: Multilayer perceptron (log CP10k) | Task: Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.971 f1-macro fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(multilayer_perceptron), paramset(log CP10k), metric(f1_macro) |
| Configuration: Multilayer perceptron (log scran) | Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.985 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(multilayer_perceptron), paramset(log scran), metric(accuracy) |
| Configuration: Multilayer perceptron (log scran) | Task: Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.985 f1 fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(multilayer_perceptron), paramset(log scran), metric(f1) |
| Configuration: Multilayer perceptron (log scran) | Task: Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.879 f1-macro fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(multilayer_perceptron), paramset(log scran), metric(f1_macro) |
| Method: Random Labels | Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.221 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(random_labels), paramset(none), metric(accuracy) |
| Method: Random Labels | Task: Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.221 f1 fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(random_labels), paramset(none), metric(f1) |
| Method: Random Labels | Task: Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.0762 f1-macro fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(random_labels), paramset(none), metric(f1_macro) |
| Configuration: scANVI (All genes) | Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Dataset subset: Pancreas (random split) (Open Problems label projection split) | 0.975 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceHuman 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 randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(scanvi), paramset(All genes), metric(accuracy) |
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2 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| description The split of Pancreas (random split) that Open Problems label projection evaluated on. The upstream dataset release is not catalogued here, so no claim is made that this matches its original splits. Context-only references | openproblems-label primary benchmark evidence No field-specific location recorded Version: v1.0.0 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| name Pancreas (random split) (Open Problems label projection split) Context-only references | openproblems-label primary benchmark evidence No field-specific location recorded Version: v1.0.0 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
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Release 2026-09-29-06401fd5b220 · Record review: source checked
Stable ID: open-problems-dataset-pancreas-random-split