XGBoost (log CP10k)
XGBoost is a gradient boosting decision tree model that learns multiple tree structures in the form of a series of input features and their values, leading to a prediction decision, and averages predictions from all its trees. Here, input features are normalised gene expression values.
Overview
XGBoost is a gradient boosting decision tree model that learns multiple tree structures in the form of a series of input features and their values, leading to a prediction decision, and averages predictions from all its trees. Here, input features are normalised gene expression values.
Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.
Evaluations and results
Release 2026-09-17-134cd1815de8 · 24 evaluations · 24 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 |
|---|---|---|
| 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 CP10k) on Open Problems label projection CENGEN-BATCH-F1: Label projection on CeNGEN (split by batch), F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection CENGEN-BATCH-F1: Label projection on CeNGEN (split by batch), F1 scoreDataset 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 | ||
| 0.834051379104698 f1 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(f1) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection CENGEN-BATCH-F1-MACRO: Label projection on CeNGEN (split by batch), Macro F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection CENGEN-BATCH-F1-MACRO: Label projection on CeNGEN (split by batch), Macro F1 scoreDataset 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 | ||
| 0.4645690989104674 f1-macro 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(f1_macro) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection CENGEN-RANDOM-ACCURACY: Label projection on CeNGEN (random split), Accuracy Configuration: XGBoost (log CP10k)Task: Open Problems label projection CENGEN-RANDOM-ACCURACY: Label projection on CeNGEN (random split), AccuracyDataset subset: CeNGEN (random split) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test randomly. Dimensions: 100955 cells, 22469 genes. 169 cell types avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.842474552821425 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_random), method(xgboost), paramset(log CP10k), metric(accuracy) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection CENGEN-RANDOM-F1: Label projection on CeNGEN (random split), F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection CENGEN-RANDOM-F1: Label projection on CeNGEN (random split), F1 scoreDataset subset: CeNGEN (random split) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test randomly. Dimensions: 100955 cells, 22469 genes. 169 cell types avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8449181894595059 f1 Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_random), method(xgboost), paramset(log CP10k), metric(f1) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection CENGEN-RANDOM-F1-MACRO: Label projection on CeNGEN (random split), Macro F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection CENGEN-RANDOM-F1-MACRO: Label projection on CeNGEN (random split), Macro F1 scoreDataset subset: CeNGEN (random split) (Open Problems label projection split) 100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test randomly. Dimensions: 100955 cells, 22469 genes. 169 cell types avg. 597±800 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.7863051512764242 f1-macro Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_random), method(xgboost), paramset(log CP10k), metric(f1_macro) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), Accuracy Configuration: XGBoost (log CP10k)Task: Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), AccuracyDataset subset: Pancreas (by batch) (Open Problems label projection split) Human 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 by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.93913984311604 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_batch), method(xgboost), paramset(log CP10k), metric(accuracy) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection PANCREAS-BATCH-F1: Label projection on Pancreas (by batch), F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection PANCREAS-BATCH-F1: Label projection on Pancreas (by batch), F1 scoreDataset subset: Pancreas (by batch) (Open Problems label projection split) Human 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 by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.9383958828902009 f1 Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_batch), method(xgboost), paramset(log CP10k), metric(f1) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection PANCREAS-BATCH-F1-MACRO: Label projection on Pancreas (by batch), Macro F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection PANCREAS-BATCH-F1-MACRO: Label projection on Pancreas (by batch), Macro F1 scoreDataset subset: Pancreas (by batch) (Open Problems label projection split) Human 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 by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.9050628910586268 f1-macro Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_batch), method(xgboost), paramset(log CP10k), metric(f1_macro) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy Configuration: XGBoost (log CP10k)Task: Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), AccuracyDataset subset: Pancreas (random split) (Open Problems label projection split) Human 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). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.9772036474164134 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(xgboost), paramset(log CP10k), metric(accuracy) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 scoreDataset subset: Pancreas (random split) (Open Problems label projection split) Human 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). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.977130825456685 f1 Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(xgboost), paramset(log CP10k), metric(f1) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 scoreDataset subset: Pancreas (random split) (Open Problems label projection split) Human 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). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.9655956850535162 f1-macro Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(xgboost), paramset(log CP10k), metric(f1_macro) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection PANCREAS-RANDOM-LABEL-NOISE-ACCURACY: Label projection on Pancreas (random split with label noise), Accuracy Configuration: XGBoost (log CP10k)Task: Open Problems label projection PANCREAS-RANDOM-LABEL-NOISE-ACCURACY: Label projection on Pancreas (random split with label noise), AccuracyDataset subset: Pancreas (random split with label noise) (Open Problems label projection split) Human 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 with 20% label noise. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.9639445300462249 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random_label_noise), method(xgboost), paramset(log CP10k), metric(accuracy) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection PANCREAS-RANDOM-LABEL-NOISE-F1: Label projection on Pancreas (random split with label noise), F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection PANCREAS-RANDOM-LABEL-NOISE-F1: Label projection on Pancreas (random split with label noise), F1 scoreDataset subset: Pancreas (random split with label noise) (Open Problems label projection split) Human 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 with 20% label noise. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.9638063508972504 f1 Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random_label_noise), method(xgboost), paramset(log CP10k), metric(f1) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection PANCREAS-RANDOM-LABEL-NOISE-F1-MACRO: Label projection on Pancreas (random split with label noise), Macro F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection PANCREAS-RANDOM-LABEL-NOISE-F1-MACRO: Label projection on Pancreas (random split with label noise), Macro F1 scoreDataset subset: Pancreas (random split with label noise) (Open Problems label projection split) Human 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 with 20% label noise. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8934197028901939 f1-macro Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random_label_noise), method(xgboost), paramset(log CP10k), metric(f1_macro) 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 CP10k) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-F1: Label projection on Tabula Muris Senis Lung (random split), F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-F1: Label projection on Tabula Muris Senis Lung (random split), F1 scoreDataset 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 | ||
| 0.8711695852376224 f1 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(f1) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-F1-MACRO: Label projection on Tabula Muris Senis Lung (random split), Macro F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-F1-MACRO: Label projection on Tabula Muris Senis Lung (random split), Macro F1 scoreDataset 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 | ||
| 0.797480077558899 f1-macro 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(f1_macro) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-LABS-ACCURACY: Label projection on Zebrafish (by laboratory), Accuracy Configuration: XGBoost (log CP10k)Task: Open Problems label projection ZEBRAFISH-LABS-ACCURACY: Label projection on Zebrafish (by laboratory), AccuracyDataset subset: Zebrafish (by laboratory) (Open Problems label projection split) 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 by laboratory. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.22440638380692876 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_labs), method(xgboost), paramset(log CP10k), metric(accuracy) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-LABS-F1: Label projection on Zebrafish (by laboratory), F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection ZEBRAFISH-LABS-F1: Label projection on Zebrafish (by laboratory), F1 scoreDataset subset: Zebrafish (by laboratory) (Open Problems label projection split) 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 by laboratory. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.27834682162039986 f1 Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_labs), method(xgboost), paramset(log CP10k), metric(f1) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-LABS-F1-MACRO: Label projection on Zebrafish (by laboratory), Macro F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection ZEBRAFISH-LABS-F1-MACRO: Label projection on Zebrafish (by laboratory), Macro F1 scoreDataset subset: Zebrafish (by laboratory) (Open Problems label projection split) 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 by laboratory. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.21439857736198084 f1-macro Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_labs), method(xgboost), paramset(log CP10k), metric(f1_macro) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-RANDOM-ACCURACY: Label projection on Zebrafish (random split), Accuracy Configuration: XGBoost (log CP10k)Task: Open Problems label projection ZEBRAFISH-RANDOM-ACCURACY: Label projection on Zebrafish (random split), AccuracyDataset subset: Zebrafish (random split) (Open Problems label projection split) 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). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.8031709203402939 accuracy Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_random), method(xgboost), paramset(log CP10k), metric(accuracy) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-RANDOM-F1: Label projection on Zebrafish (random split), F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection ZEBRAFISH-RANDOM-F1: Label projection on Zebrafish (random split), F1 scoreDataset subset: Zebrafish (random split) (Open Problems label projection split) 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). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.7995257960670158 f1 Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_random), method(xgboost), paramset(log CP10k), metric(f1) Source checking is not independent reproduction. |
| XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-RANDOM-F1-MACRO: Label projection on Zebrafish (random split), Macro F1 score Configuration: XGBoost (log CP10k)Task: Open Problems label projection ZEBRAFISH-RANDOM-F1-MACRO: Label projection on Zebrafish (random split), Macro F1 scoreDataset subset: Zebrafish (random split) (Open Problems label projection split) 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). Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.6814826306177239 f1-macro Unit: fraction · Direction: higher | Uncertainty: Not reported Scored: Not reported · Eligible: Not reported | source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_random), method(xgboost), paramset(log CP10k), metric(f1_macro) Source checking is not independent reproduction. |
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Release 2026-09-17-134cd1815de8 · Record review: source checked
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Stable ID: open-problems-method-xgboost-log-cp10k
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Related records
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- model: XGBoost (log CP10k) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-F1: Label projection on Tabula Muris Senis Lung (random split), F1 score
- model: XGBoost (log CP10k) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-F1-MACRO: Label projection on Tabula Muris Senis Lung (random split), Macro F1 score
- model: XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-LABS-ACCURACY: Label projection on Zebrafish (by laboratory), Accuracy
- model: XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-LABS-F1: Label projection on Zebrafish (by laboratory), F1 score
- model: XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-LABS-F1-MACRO: Label projection on Zebrafish (by laboratory), Macro F1 score
- model: XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-RANDOM-ACCURACY: Label projection on Zebrafish (random split), Accuracy
- model: XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-RANDOM-F1: Label projection on Zebrafish (random split), F1 score
- model: XGBoost (log CP10k) on Open Problems label projection ZEBRAFISH-RANDOM-F1-MACRO: Label projection on Zebrafish (random split), Macro F1 score