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1 evaluation · 1 result. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: Hyenadna 1 mf (Manzo et al. 2025) | Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025) | 0.118 pearson-correlation unitless · higher Uncertainty: SE 0.056. Standard error as printed in brackets; its basis is not defined in the caption Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceHyenadna 1 mf on K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' |
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regulatory-variant-20261009-protocol-manzo2025-k562-pearson
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18 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.comparison.adaptation Conflicting in the source: Table 2 says HyenaDNA was used inference-only with inputs padded to 32,768 tokens; Section 4.2 lists HyenaDNA among models fine-tuned per cell line with the Trainer API. Variant effect is the log2 ratio of alternative to reference scores. Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 |
| attributes.comparison.aggregation As printed per cell line Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 |
| attributes.comparison.budget Not reported Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 |
| attributes.comparison.dataset_version As published Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 |
| attributes.comparison.inputs 1 kb reference and alternative sequences centred on the SNP Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 |
| attributes.comparison.metric_implementation Pearson correlation of predicted and measured log2 fold-change Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 |
| attributes.comparison.population 19321 SNPs Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 |
| attributes.comparison.protocol_id regulatory-variant-20261009-protocol-manzo2025-k562-pearson Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 |
| attributes.comparison.split Per cell line Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 |
| attributes.origin independent_paper Context-only references | Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)' Version: Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML | 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 2026-10-10-6e93f504adfc · Record review: source checked
Stable ID: regulatory-variant-20261009-eval-manzo2025-k562-hyenadna-1-mf