Open Problems label projection evaluation of Logistic regression (log scran) on Label projection on Zebrafish (random split), Accuracy, scored with Accuracy.
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1 evaluation · 1 result. Different protocols are not a single leaderboard.
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| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: Logistic regression (log scran) | Task: Open Problems label projection ZEBRAFISH-RANDOM-ACCURACY: Label projection on Zebrafish (random split), Accuracy Dataset subset: Zebrafish (random split) (Open Problems label projection split) | 0.843 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and source90k cells from zebrafish embryos throughout the first day of development, with and without a knockout of chordin, an important developmental gene. Split into train/test randomly. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type). Aggregation: Not reported openproblems-label primary benchmark evidence · results, dataset(zebrafish_random), method(logistic_regression), paramset(log scran), metric(accuracy) |
Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.
90k cells from zebrafish embryos throughout the first day of development, with and without a knockout of chordin, an important developmental gene. Split into train/test randomly. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type).
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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(zebrafish_random), method(logistic_regression), 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-zebrafish-random-accuracy Context-only references | openproblems-label primary benchmark evidence results, dataset(zebrafish_random), method(logistic_regression), 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(zebrafish_random), method(logistic_regression), 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 90k cells from zebrafish embryos throughout the first day of development, with and without a knockout of chordin, an important developmental gene. Split into train/test randomly. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type). Context-only references | openproblems-label primary benchmark evidence results, dataset(zebrafish_random), method(logistic_regression), 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(zebrafish_random), method(logistic_regression), paramset(log scran), metric(accuracy) Context-only references | openproblems-label primary benchmark evidence results, dataset(zebrafish_random), method(logistic_regression), 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 Logistic regression (log scran) on Label projection on Zebrafish (random split), Accuracy, scored with Accuracy. Context-only references | openproblems-label primary benchmark evidence results, dataset(zebrafish_random), method(logistic_regression), 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-zebrafish-random-accuracy Context-only references | openproblems-label primary benchmark evidence results, dataset(zebrafish_random), method(logistic_regression), 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-zebrafish-random-split Context-only references | openproblems-label primary benchmark evidence results, dataset(zebrafish_random), method(logistic_regression), 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-logistic-regression-log-scran Context-only references | openproblems-label primary benchmark evidence results, dataset(zebrafish_random), method(logistic_regression), 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 Logistic regression (log scran) on Open Problems label projection ZEBRAFISH-RANDOM-ACCURACY: Label projection on Zebrafish (random split), Accuracy Context-only references | openproblems-label primary benchmark evidence results, dataset(zebrafish_random), method(logistic_regression), 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. |
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Release 2026-09-29-06401fd5b220 · Record review: source checked
Stable ID: open-problems-evaluation-logistic-regression-log-scran-zebrafish-random-accuracy