Published comparison transcribed from the pinned source; not reproduced.
1 evaluation · 6 results. Different protocols are not a single leaderboard.
Protocol: PLABench KIBA, warm split · Dataset: KIBA warm test set (PLABench)
Sorted by Concordance index (PLABench KIBA-warm) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.
| Tested configuration | Concordance index (PLABench KIBA-warm) | Modified squared correlation (PLABench KIBA-warm) | MSE (PLABench KIBA-warm) | Pearson (PLABench KIBA-warm) | RMSE (PLABench KIBA-warm) | Spearman (PLABench KIBA-warm) |
|---|---|---|---|---|---|---|
| DeepDTA (retrained on Davis and KIBA, PLABench)Evaluation | 0.831 | 0.657 | 0.23 | 0.818 | 0.479 | 0.798 |
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench) | 0.831 Concordance index (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'CI' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench) | 0.23 MSE (PLABench KIBA-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'MSE' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench) | 0.818 Pearson (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'Pearson' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench) | 0.657 Modified squared correlation (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'rm2' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench) | 0.479 RMSE (PLABench KIBA-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'RMSE' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench) | 0.798 Spearman (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'Spearman' (text-layer line 439) |
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18 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Comparison: adaptation Retrained by the benchmark authors Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: aggregation Not reported Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | missing or unspecified No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: budget Not reported Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | missing or unspecified No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: dataset version PLABench bioRxiv v1 Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: inputs Protein sequence and ligand SMILES Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: metric implementation As defined in Methods, 'Evaluation metrics' Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: population Not reported Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | missing or unspecified No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: protocol id lit-interactions-20261011-leakctl-protocol-kiba-warm Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: split KIBA-warm Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Origin independent_paper Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2 row 'DeepDTA', column group 'strategy 'Warm split', dataset 'KIBA'' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded independent paper Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Release 2026-10-23-5347695500ed · Record review: source checked
Stable ID: lit-interactions-20261011-leakctl-eval-deepdta-kiba-warm