Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6
Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) · Peer-reviewed
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- reported_finding: amp-feng-20261007-protocol-promoter-nontata: Reported finding Baseline CNN trained from scratch on Promoter Arabidopsis NonTATA: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): Caduceus-Ph, DNABERT-2, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 2. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter Arabidopsis NonTATA')
- reported_finding: amp-feng-20261007-protocol-promoter-tata: Reported finding Baseline CNN trained from scratch on Promoter Arabidopsis TATA: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): Caduceus-Ph, DNABERT-2, GROVER, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 2. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter Arabidopsis TATA')
- reported_finding: amp-feng-20261007-protocol-splice-acceptor: Reported finding Baseline CNN trained from scratch on Acceptor: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): Caduceus-Ph, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Acceptors')
- reported_finding: amp-feng-20261007-protocol-splice-donor: Reported finding Baseline CNN trained from scratch on Donor: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): Caduceus-Ph, DNABERT-2, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Donors')
- reported_finding: feng-dna-fm-20261013-protocol-t1-coding: Reported finding Baseline CNN trained from scratch on Coding: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): DNABERT-2, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: Caduceus-Ph, GROVER. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Coding')
- reported_finding: feng-dna-fm-20261013-protocol-t1-dnase-i-hypersensitive: Reported finding Baseline CNN trained from scratch on DNase I Hypersensitive: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): None. Supplementary Data 2 lists the models that significantly outperformed the CNN: Caduceus-Ph, DNABERT-2. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'DNase I Hypersensitive')
- reported_finding: feng-dna-fm-20261013-protocol-t1-enhancer: Reported finding Baseline CNN trained from scratch on Enhancer: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): None. Supplementary Data 2 lists the models that significantly outperformed the CNN: DNABERT-2, NT-v2. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Enhancer')
- reported_finding: feng-dna-fm-20261013-protocol-t1-enhancer-cohn: Reported finding Baseline CNN trained from scratch on Enhancer Cohn: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): HyenaDNA. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Enhancer Cohn')
- reported_finding: feng-dna-fm-20261013-protocol-t1-enhancer-ensembl: Reported finding Baseline CNN trained from scratch on Enhancer Ensembl: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): None. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Enhancer Ensembl')
- reported_finding: feng-dna-fm-20261013-protocol-t1-human-tfbs-1: Reported finding Baseline CNN trained from scratch on Human TFBS 1: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): None. Supplementary Data 2 lists the models that significantly outperformed the CNN: Caduceus-Ph, GROVER. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Human TFBS 1')
- reported_finding: feng-dna-fm-20261013-protocol-t1-human-tfbs-2: Reported finding Baseline CNN trained from scratch on Human TFBS 2: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): None. Supplementary Data 2 lists the models that significantly outperformed the CNN: Caduceus-Ph, GROVER. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Human TFBS 2')
- reported_finding: feng-dna-fm-20261013-protocol-t1-human-tfbs-3: Reported finding Baseline CNN trained from scratch on Human TFBS 3: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): Caduceus-Ph, DNABERT-2, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Human TFBS 3')
- reported_finding: feng-dna-fm-20261013-protocol-t1-human-tfbs-4: Reported finding Baseline CNN trained from scratch on Human TFBS 4: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): DNABERT-2, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: Caduceus-Ph, GROVER. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Human TFBS 4')
- reported_finding: feng-dna-fm-20261013-protocol-t1-human-tfbs-5: Reported finding Baseline CNN trained from scratch on Human TFBS 5: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): None. Supplementary Data 2 lists the models that significantly outperformed the CNN: Caduceus-Ph, GROVER. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Human TFBS 5')
- reported_finding: feng-dna-fm-20261013-protocol-t1-open-chromatin-region: Reported finding Baseline CNN trained from scratch on Open chromatin region: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): DNABERT-2, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Open Chromatin Region')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-all-70-bps: Reported finding Baseline CNN trained from scratch on Promoter All 70 bps: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): Caduceus-Ph, DNABERT-2, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter All 70bps')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-all-300-bps: Reported finding Baseline CNN trained from scratch on Promoter All 300 bps: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): DNABERT-2, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter All 300bps')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-gm12878: Reported finding Baseline CNN trained from scratch on Promoter GM12878: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): None. Supplementary Data 2 lists the models that significantly outperformed the CNN: Caduceus-Ph, DNABERT-2, GROVER, NT-v2. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter GM12878')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-hela-s3: Reported finding Baseline CNN trained from scratch on Promoter Hela-S3: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): None. Supplementary Data 2 lists the models that significantly outperformed the CNN: Caduceus-Ph, DNABERT-2, GROVER, NT-v2. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter Hela-S3')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-huvec: Reported finding Baseline CNN trained from scratch on Promoter HUVEC: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): None. Supplementary Data 2 lists the models that significantly outperformed the CNN: Caduceus-Ph, DNABERT-2, GROVER, NT-v2. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter HUVEC')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-nhek: Reported finding Baseline CNN trained from scratch on Promoter NHEK: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter NHEK')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-nontata-70-bps: Reported finding Baseline CNN trained from scratch on Promoter NonTATA 70 bps: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): DNABERT-2, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter NonTATA 70bps')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-nontata-251-bps: Reported finding Baseline CNN trained from scratch on Promoter NonTATA 251 bps: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): DNABERT-2, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter NonTATA 251bps')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-nontata-300-bps: Reported finding Baseline CNN trained from scratch on Promoter NonTATA 300 bps: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): Caduceus-Ph, DNABERT-2, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter NonTATA 300bps')
- reported_finding: feng-dna-fm-20261013-protocol-t1-promoter-tata-70-bps: Reported finding Baseline CNN trained from scratch on Promoter TATA 70 bps: Supplementary Data 1 lists the DNA foundation models the CNN significantly outperformed (one-sided DeLong p<0.01): Caduceus-Ph, DNABERT-2, GROVER, HyenaDNA, NT-v2. Supplementary Data 2 lists the models that significantly outperformed the CNN: None. The CNN's AUC is not printed, so it has no result record; the foundation-model AUCs are in Table 1. (Supplementary Data 1 and Supplementary Data 2, row 'Promoter TATA 70bps')
Models, benchmarks and other records
Protocols (48)
- Feng A.Thaliana 4mC sequence classification
- Feng C.Elegans 4mC sequence classification
- Feng Coding sequence classification
- Feng D.Melanogaster 4mC sequence classification
- Feng DNase I Hypersensitive sequence classification
- Feng E.Coli 4mC sequence classification
- Feng Enhancer Cohn sequence classification
- Feng Enhancer Ensembl sequence classification
- Feng Enhancer sequence classification
- Feng G.Pickeringii 4mC sequence classification
- Feng G.Subterraneus 4mC sequence classification
- Feng Human 5mC sequence classification
- Feng Human 6 mA sequence classification
- Feng Human TFBS 1 sequence classification
- Feng Human TFBS 2 sequence classification
- Feng Human TFBS 3 sequence classification
- Feng Human TFBS 4 sequence classification
- Feng Human TFBS 5 sequence classification
- Feng Human vs worm sequence classification
- Feng Mouse TFBS 1 sequence classification
- Feng Mouse TFBS 2 sequence classification
- Feng Mouse TFBS 3 sequence classification
- Feng Mouse TFBS 4 sequence classification
- Feng Mouse TFBS 5 sequence classification
- Feng Open chromatin region sequence classification
Datasets (47)
- Feng A.Thaliana 4mC dataset
- Feng C.Elegans 4mC dataset
- Feng Coding dataset
- Feng D.Melanogaster 4mC dataset
- Feng DNase I Hypersensitive dataset
- Feng E.Coli 4mC dataset
- Feng Enhancer Cohn dataset
- Feng Enhancer dataset
- Feng Enhancer Ensembl dataset
- Feng G.Pickeringii 4mC dataset
- Feng G.Subterraneus 4mC dataset
- Feng Human 6 mA dataset
- Feng Human TFBS 1 dataset
- Feng Human TFBS 2 dataset
- Feng Human TFBS 3 dataset
- Feng Human TFBS 4 dataset
- Feng Human TFBS 5 dataset
- Feng Human vs worm dataset
- Feng Mouse TFBS 1 dataset
- Feng Mouse TFBS 2 dataset
- Feng Mouse TFBS 3 dataset
- Feng Mouse TFBS 4 dataset
- Feng Mouse TFBS 5 dataset
- Feng Open chromatin region dataset
- Feng Promoter All 70 bps dataset
Evaluations (59)
- AlphaGenome, output tracks eQTL per-test-group evaluation
- AlphaGenome, output tracks ipaQTL per-test-group evaluation
- AlphaGenome, output tracks paQTL per-test-group evaluation
- AlphaGenome, output tracks sQTL per-test-group evaluation
- Caduceus-Ph eQTL per-test-group evaluation
- Caduceus-Ph ipaQTL per-test-group evaluation
- Caduceus-Ph paQTL per-test-group evaluation
- Caduceus-Ph Pathogenic variants vs common per-test-group evaluation
- Caduceus-Ph sQTL per-test-group evaluation
- Caduceus-Ph, long sequence eQTL per-test-group evaluation
- Caduceus-Ph, long sequence ipaQTL per-test-group evaluation
- Caduceus-Ph, long sequence paQTL per-test-group evaluation
- Caduceus-Ph, long sequence Pathogenic variants vs common per-test-group evaluation
- Caduceus-Ph, long sequence sQTL per-test-group evaluation
- DNABERT-2 eQTL per-test-group evaluation
- DNABERT-2 ipaQTL per-test-group evaluation
- DNABERT-2 paQTL per-test-group evaluation
- DNABERT-2 Pathogenic variants vs common per-test-group evaluation
- DNABERT-2 sQTL per-test-group evaluation
- Enformer, hidden states eQTL per-test-group evaluation
- Enformer, hidden states ipaQTL per-test-group evaluation
- Enformer, hidden states paQTL per-test-group evaluation
- Enformer, hidden states Pathogenic variants vs common per-test-group evaluation
- Enformer, hidden states sQTL per-test-group evaluation
- Enformer, output tracks eQTL per-test-group evaluation
Evidence
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26 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Artifact SHA-256 4804c801e0e054eca5f776617c18a6a0cb31d6ce3d2a7a52f70e4dda5b3abd7a Source metadata | Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Artifact url https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-025-65823-8/MediaObjects/41467_2025_65823_MOESM3_ESM.xlsm Source metadata | Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Doi 10.1038/s41467-025-65823-8 Source metadata | Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Licence CC-BY-4.0 Source metadata | Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Limitations2 values
| Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Media type application/vnd.ms-excel.sheet.macroEnabled.12 Source metadata | Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Publication status peer_reviewed Source metadata | Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Retrieved at 2026-10-13T14:08:10Z Source metadata | Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Review: artifact sha256 4804c801e0e054eca5f776617c18a6a0cb31d6ce3d2a7a52f70e4dda5b3abd7a Source metadata | Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Review: method note Re-downloaded and matched; the archived artifacts/MOESM3_ESM.xlsm.gz decompresses to the same bytes. Read all seven sheets. Source metadata | Benchmarking DNA foundation models for genomic and genetic tasks: Supplementary Data 1-6 No field-specific location recorded Version: Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm) | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-11-02-a7f03c9e55a5 · Record review: source checked
Supplementary Data workbook of Feng et al. 2025 (Nature Communications 16:10780), retrieved and hashed for rewire-benchmark-data#19.
Technical metadata and extraction receipts
Stable ID: feng-dna-fm-20261013-source-supplementary-data
- areas
- dna-genomes
- contexts
- research
- doi
- 10.1038/s41467-025-65823-8
- publication status
- peer_reviewed
- licence
- CC-BY-4.0
- url
- https://doi.org/10.1038/s41467-025-65823-8
- retrieved at
- 2026-10-13T14:08:10Z
- artifact url
- https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-025-65823-8/MediaObjects/41467_2025_65823_MOESM3_ESM.xlsm
- artifact sha256
- 4804c801e0e054eca5f776617c18a6a0cb31d6ce3d2a7a52f70e4dda5b3abd7a
- media type
- application/vnd.ms-excel.sheet.macroEnabled.12
- version
- Nature Communications 16, 10780 (2025); Supplementary Data 1-6 workbook (MOESM3, .xlsm)
- limitations
- Supplementary Data 1 and 2 list, per dataset, which models the baseline CNN significantly beat and which beat the CNN (one-sided DeLong p<0.01). The CNN's own AUC values are not printed anywhere in the article or supplement.; Supplementary Data 6 gives Enhancer Ensembl the same training and test sizes as Enhancer and a three-class label distribution, although Table 1 reports it as a binary AUC task.
- review
- method: source-hash-verification; ai-assisted-source-review; method note: Re-downloaded and matched; the archived artifacts/MOESM3_ESM.xlsm.gz decompresses to the same bytes. Read all seven sheets.; reviewer: claude; reviewer note: Independent Claude (Opus 5.5) review agent, separate from the extraction agent feng-19 that built this batch. Automated review only; no human review claimed. Transcription, not reproduction.; reviewed at: 2026-10-13T14:40:00Z; artifact sha256: 4804c801e0e054eca5f776617c18a6a0cb31d6ce3d2a7a52f70e4dda5b3abd7a; retrieval url: https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-025-65823-8/MediaObjects/41467_2025_65823_MOESM3_ESM.xlsm; note: Identity, version, licence and limitations checked against the artifact.