Configuration

UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)

Configuration as run in the cited comparison.

Overview

Configuration as run in the cited comparison.

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

Evaluations and results

4 evaluations · 24 results. Different protocols are not a single leaderboard.

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.802 accuracy fraction · higher Uncertainty: 95% CI 0.794396877940584 to 0.808787387417664. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 13 (feat 'Length', ichorcna_strat '[0, 0.03]', .metric 'Accuracy'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.907 auprc unitless · higher Uncertainty: 95% CI 0.899925572748059 to 0.913771866988121. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 9 (feat 'Length', ichorcna_strat '[0, 0.03]', .metric 'AUPRC'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.873 auroc unitless · higher Uncertainty: 95% CI 0.866644367451426 to 0.879415132656203. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 8 (feat 'Length', ichorcna_strat '[0, 0.03]', .metric 'AUROC'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.838 f1-score fraction · higher Uncertainty: 95% CI 0.831411030016281 to 0.843953731080608. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 12 (feat 'Length', ichorcna_strat '[0, 0.03]', .metric 'F1'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.824 recall fraction · higher Uncertainty: 95% CI 0.816103747393066 to 0.831907394430797. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 10 (feat 'Length', ichorcna_strat '[0, 0.03]', .metric 'Sensitivity'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.765 specificity fraction · higher Uncertainty: 95% CI 0.751948581446746 to 0.778393430922037. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 11 (feat 'Length', ichorcna_strat '[0, 0.03]', .metric 'Specificity'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.837 accuracy fraction · higher Uncertainty: 95% CI 0.830053630363036 to 0.844060328091633. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 49 (feat 'Length', ichorcna_strat '(0.03, 0.1]', .metric 'Accuracy'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.842 auprc unitless · higher Uncertainty: 95% CI 0.82950844424155 to 0.854683890616125. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 45 (feat 'Length', ichorcna_strat '(0.03, 0.1]', .metric 'AUPRC'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.896 auroc unitless · higher Uncertainty: 95% CI 0.888753567411303 to 0.903684467251858. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 44 (feat 'Length', ichorcna_strat '(0.03, 0.1]', .metric 'AUROC'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.756 f1-score fraction · higher Uncertainty: 95% CI 0.743425392707668 to 0.768290931087008. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 48 (feat 'Length', ichorcna_strat '(0.03, 0.1]', .metric 'F1'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.713 recall fraction · higher Uncertainty: 95% CI 0.695455062998846 to 0.732359127583684. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 46 (feat 'Length', ichorcna_strat '(0.03, 0.1]', .metric 'Sensitivity'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.906 specificity fraction · higher Uncertainty: 95% CI 0.896113876598381 to 0.916368038535761. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 47 (feat 'Length', ichorcna_strat '(0.03, 0.1]', .metric 'Specificity'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.846 accuracy fraction · higher Uncertainty: 95% CI 0.839969664545957 to 0.852574965496332. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 121 (feat 'Length', ichorcna_strat 'all', .metric 'Accuracy'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.959 auprc unitless · higher Uncertainty: 95% CI 0.956616305569071 to 0.962125287167047. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 117 (feat 'Length', ichorcna_strat 'all', .metric 'AUPRC'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.902 auroc unitless · higher Uncertainty: 95% CI 0.897435301716713 to 0.90763132672471. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 116 (feat 'Length', ichorcna_strat 'all', .metric 'AUROC'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.893 f1-score fraction · higher Uncertainty: 95% CI 0.887486231570293 to 0.898171325142905. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 120 (feat 'Length', ichorcna_strat 'all', .metric 'F1'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.872 recall fraction · higher Uncertainty: 95% CI 0.863197952080612 to 0.881540138517843. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 118 (feat 'Length', ichorcna_strat 'all', .metric 'Sensitivity'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.773 specificity fraction · higher Uncertainty: 95% CI 0.762694726551668 to 0.784395220186179. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 119 (feat 'Length', ichorcna_strat 'all', .metric 'Specificity'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.924 accuracy fraction · higher Uncertainty: 95% CI 0.918373996691621 to 0.930801658936716. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 85 (feat 'Length', ichorcna_strat '(0.1, 1]', .metric 'Accuracy'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.964 auprc unitless · higher Uncertainty: 95% CI 0.95889962663933 to 0.969806495334019. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 81 (feat 'Length', ichorcna_strat '(0.1, 1]', .metric 'AUPRC'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.972 auroc unitless · higher Uncertainty: 95% CI 0.96804392511071 to 0.977108756594996. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 80 (feat 'Length', ichorcna_strat '(0.1, 1]', .metric 'AUROC'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.895 f1-score fraction · higher Uncertainty: 95% CI 0.88633382306218 to 0.903773740355175. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 84 (feat 'Length', ichorcna_strat '(0.1, 1]', .metric 'F1'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.862 recall fraction · higher Uncertainty: 95% CI 0.849063575481367 to 0.877182843347527. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 82 (feat 'Length', ichorcna_strat '(0.1, 1]', .metric 'Sensitivity'), column D 'mean'
Configuration: UNITE XGBoost, Fragment length (Len) (Wang et al. 2026)	Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026) Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples	0.962 specificity fraction · higher Uncertainty: 95% CI 0.955098758918867 to 0.968847189029617. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source UNITE XGBoost Fragment length (Len), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 83 (feat 'Length', ichorcna_strat '(0.1, 1]', .metric 'Specificity'), column D 'mean'

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A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing · Original source · Science Advances 12(28):eady9432, published 2026-07-10; PMC13353424 full-text XML
Wang et al. 2026, Data file S2 (model scores and summary statistics) · Original source · ady9432_data_file_s2.xlsx inside sciadv.ady9432_data_files_s1_and_s2.zip, PMC open-access copy PMC13353424.1

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Stable ID: ctdnafrag-20261009-config-wang2026-unite-xgb-len

areas: dna-genomes
contexts: clinical_research
method types: supervised_machine_learning
reported name: Length
foundation model eligible: false
source locator: Data file S2 sheet STATS_xgb_x1-x6 column 'feat'; Methods P49
missing metadata: version: reason: unreported; note: No UNITE release or code commit is printed for these cross-validation models
parameters: Features: Fragment length (Len). XGBoost with nested cross-validation (StratifiedGroupKFold, randomized grid search); keras v3.3.3 and scikit-learn v1.4.2.

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