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1 evaluation · 6 results. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| 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 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 checkedMethods, coverage and sourceUNITE 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 checkedMethods, coverage and sourceUNITE 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 checkedMethods, coverage and sourceUNITE 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 checkedMethods, coverage and sourceUNITE 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 checkedMethods, coverage and sourceUNITE 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 checkedMethods, coverage and sourceUNITE 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' |
Source checking is not independent reproduction. Release 2026-10-09-ba02f2f4a36e.
ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct
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One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
36 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.comparison.adaptation Model trained per outer fold with inner hyperparameter search Context-only references | A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Science Advances 12(28):eady9432, published 2026-07-10; PMC13353424 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.comparison.adaptation Model trained per outer fold with inner hyperparameter search Context-only references | Wang et al. 2026, Data file S2 (model scores and summary statistics) Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: ady9432_data_file_s2.xlsx inside sciadv.ady9432_data_files_s1_and_s2.zip, PMC open-access copy PMC13353424.1 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: artifact_sha256 is the zip as served; the member ady9432_data_file_s2.xlsx has SHA-256 32ae4ff3b7e1c85fa8662a57b45f77330e56e475f996f6489f25e36a81de65aa Archive member: ady9432_data_file_s2.xlsx |
| attributes.comparison.aggregation Mean, median, SD, 95% CI and SEM over 50 outer test folds Context-only references | A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Science Advances 12(28):eady9432, published 2026-07-10; PMC13353424 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.comparison.aggregation Mean, median, SD, 95% CI and SEM over 50 outer test folds Context-only references | Wang et al. 2026, Data file S2 (model scores and summary statistics) Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: ady9432_data_file_s2.xlsx inside sciadv.ady9432_data_files_s1_and_s2.zip, PMC open-access copy PMC13353424.1 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: artifact_sha256 is the zip as served; the member ady9432_data_file_s2.xlsx has SHA-256 32ae4ff3b7e1c85fa8662a57b45f77330e56e475f996f6489f25e36a81de65aa Archive member: ady9432_data_file_s2.xlsx |
| attributes.comparison.budget Not reported Context-only references | A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Science Advances 12(28):eady9432, published 2026-07-10; PMC13353424 full-text XML | missing or unspecified No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.comparison.budget Not reported Context-only references | Wang et al. 2026, Data file S2 (model scores and summary statistics) Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: ady9432_data_file_s2.xlsx inside sciadv.ady9432_data_files_s1_and_s2.zip, PMC open-access copy PMC13353424.1 | missing or unspecified No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: artifact_sha256 is the zip as served; the member ady9432_data_file_s2.xlsx has SHA-256 32ae4ff3b7e1c85fa8662a57b45f77330e56e475f996f6489f25e36a81de65aa Archive member: ady9432_data_file_s2.xlsx |
| attributes.comparison.dataset_version Wang et al. 2026 cross-validation set Context-only references | A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Science Advances 12(28):eady9432, published 2026-07-10; PMC13353424 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.comparison.dataset_version Wang et al. 2026 cross-validation set Context-only references | Wang et al. 2026, Data file S2 (model scores and summary statistics) Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: ady9432_data_file_s2.xlsx inside sciadv.ady9432_data_files_s1_and_s2.zip, PMC open-access copy PMC13353424.1 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: artifact_sha256 is the zip as served; the member ady9432_data_file_s2.xlsx has SHA-256 32ae4ff3b7e1c85fa8662a57b45f77330e56e475f996f6489f25e36a81de65aa Archive member: ady9432_data_file_s2.xlsx |
| attributes.comparison.inputs Fragment length (Len) from 0.1x sWGS Context-only references | A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Science Advances 12(28):eady9432, published 2026-07-10; PMC13353424 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.comparison.inputs Fragment length (Len) from 0.1x sWGS Context-only references | Wang et al. 2026, Data file S2 (model scores and summary statistics) Data file S2 sheet STATS_xgb_x1-x6, rows with feat 'Length' and ichorcna_strat '(0.1, 1]' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: ady9432_data_file_s2.xlsx inside sciadv.ady9432_data_files_s1_and_s2.zip, PMC open-access copy PMC13353424.1 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: artifact_sha256 is the zip as served; the member ady9432_data_file_s2.xlsx has SHA-256 32ae4ff3b7e1c85fa8662a57b45f77330e56e475f996f6489f25e36a81de65aa Archive member: ady9432_data_file_s2.xlsx |
Release 2026-10-09-ba02f2f4a36e · Record review: source checked
Stable ID: ctdnafrag-20261009-eval-wang2026-len-tf-over-10pct