Dataset subset

ClinVar stop-gains not expected to undergo NMD (Brandes et al. 2023)

Stop-gain variants for which the 50 bp rule predicts no nonsense-mediated decay: 3,672 pathogenic and 147 benign.

Evaluation results

3 evaluations · 3 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: ESM1b minimum-LLR stop-gain score (Brandes et al. 2023)	Protocol: ClinVar stop-gain pathogenicity by NMD status, ROC-AUC (Brandes et al. 2023 Fig. 6d, Supplementary Table 2) Dataset subset: ClinVar stop-gains not expected to undergo NMD (Brandes et al. 2023)	0.734 AUROC (ROC-AUC, pathogenic versus benign ClinVar stop-gains not expected to undergo NMD (50 bp rule); zero-shot) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source ESM1b-minLLR on stop-gains not expected to undergo NMD (50 bp rule) (Brandes et al. 2023) gfm-guides-20261014-esm1b-protocol-clinvar-stop-gains Aggregation: Not reported Brandes et al. 2023 Supplementary Table 2: full benchmark evaluations of ESM1b and all other methods · Supplementary Table 2 sheet 'Table_of_results_stop_gains' cell B2, row 'ESM1b-minLLR', column 'AUC_no_NMD'
Method: Number of residues lost (stop-gain baseline)	Protocol: ClinVar stop-gain pathogenicity by NMD status, ROC-AUC (Brandes et al. 2023 Fig. 6d, Supplementary Table 2) Dataset subset: ClinVar stop-gains not expected to undergo NMD (Brandes et al. 2023)	0.65 AUROC (ROC-AUC, pathogenic versus benign ClinVar stop-gains not expected to undergo NMD (50 bp rule); zero-shot) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source num. AA lost on stop-gains not expected to undergo NMD (50 bp rule) (Brandes et al. 2023) gfm-guides-20261014-esm1b-protocol-clinvar-stop-gains Aggregation: Not reported Brandes et al. 2023 Supplementary Table 2: full benchmark evaluations of ESM1b and all other methods · Supplementary Table 2 sheet 'Table_of_results_stop_gains' cell B3, row 'num. AA lost', column 'AUC_no_NMD'
Method: Percentage of residues lost (stop-gain baseline)	Protocol: ClinVar stop-gain pathogenicity by NMD status, ROC-AUC (Brandes et al. 2023 Fig. 6d, Supplementary Table 2) Dataset subset: ClinVar stop-gains not expected to undergo NMD (Brandes et al. 2023)	0.6 AUROC (ROC-AUC, pathogenic versus benign ClinVar stop-gains not expected to undergo NMD (50 bp rule); zero-shot) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source pct. AA lost on stop-gains not expected to undergo NMD (50 bp rule) (Brandes et al. 2023) gfm-guides-20261014-esm1b-protocol-clinvar-stop-gains Aggregation: Not reported Brandes et al. 2023 Supplementary Table 2: full benchmark evaluations of ESM1b and all other methods · Supplementary Table 2 sheet 'Table_of_results_stop_gains' cell B4, row 'pct. AA lost', column 'AUC_no_NMD'

Source checking is not independent reproduction. Release 2026-10-22-1b7cf027e4f6.

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Release 2026-10-22-1b7cf027e4f6 · Evidence verified: Not verified

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Evidence

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Evidence table

Inspect claims, sources and review details

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24 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-22-1b7cf027e4f6
Property and statement	Original source and location	Review and provenance
Positive count 3672 Context-only references	Genome-wide prediction of disease variant effects with a deep protein language model (Brandes et al., Nature Genetics 2023) Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:14Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.positive_count` Source artifact SHA-256: `919ca366369efbe7e0880565192de127375edddedb1aa43ad023dec612bb4a04` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-pmc10484790.xml.gz Inspected artifact
Positive count 3672 Context-only references	Brandes et al. 2023 Supplementary Information (Supplementary Table 1 and Methods) Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:21Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.positive_count` Source artifact SHA-256: `30f1c2713875c7cec40f0beee19864840bc55326ddf68918841f93f8bb897c2a` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-supplementary-information.pdf.gz Inspected artifact
Positive count 3672 Context-only references	Brandes et al. 2023 Supplementary Table 2: full benchmark evaluations of ESM1b and all other methods Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:21Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.positive_count` Source artifact SHA-256: `093c32e4156a801c0dd809a437c87818a4f1d04df92e037cf40222471a3e72e2` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-supplementary-table-2.xlsx.gz Inspected artifact
Scored count 3819 Context-only references	Genome-wide prediction of disease variant effects with a deep protein language model (Brandes et al., Nature Genetics 2023) Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:14Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.scored_count` Source artifact SHA-256: `919ca366369efbe7e0880565192de127375edddedb1aa43ad023dec612bb4a04` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-pmc10484790.xml.gz Inspected artifact
Scored count 3819 Context-only references	Brandes et al. 2023 Supplementary Information (Supplementary Table 1 and Methods) Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:21Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.scored_count` Source artifact SHA-256: `30f1c2713875c7cec40f0beee19864840bc55326ddf68918841f93f8bb897c2a` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-supplementary-information.pdf.gz Inspected artifact
Scored count 3819 Context-only references	Brandes et al. 2023 Supplementary Table 2: full benchmark evaluations of ESM1b and all other methods Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:21Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.scored_count` Source artifact SHA-256: `093c32e4156a801c0dd809a437c87818a4f1d04df92e037cf40222471a3e72e2` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-supplementary-table-2.xlsx.gz Inspected artifact
Source dataset label ClinVar stop-gains Context-only references	Genome-wide prediction of disease variant effects with a deep protein language model (Brandes et al., Nature Genetics 2023) Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:14Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_dataset_label` Source artifact SHA-256: `919ca366369efbe7e0880565192de127375edddedb1aa43ad023dec612bb4a04` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-pmc10484790.xml.gz Inspected artifact
Source dataset label ClinVar stop-gains Context-only references	Brandes et al. 2023 Supplementary Information (Supplementary Table 1 and Methods) Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:21Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_dataset_label` Source artifact SHA-256: `30f1c2713875c7cec40f0beee19864840bc55326ddf68918841f93f8bb897c2a` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-supplementary-information.pdf.gz Inspected artifact
Source dataset label ClinVar stop-gains Context-only references	Brandes et al. 2023 Supplementary Table 2: full benchmark evaluations of ESM1b and all other methods Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:21Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_dataset_label` Source artifact SHA-256: `093c32e4156a801c0dd809a437c87818a4f1d04df92e037cf40222471a3e72e2` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-supplementary-table-2.xlsx.gz Inspected artifact
Source location Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Context-only references	Genome-wide prediction of disease variant effects with a deep protein language model (Brandes et al., Nature Genetics 2023) Original source ↗ Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10) Retrieved: 2026-10-14T12:03:14Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_locator` Source artifact SHA-256: `919ca366369efbe7e0880565192de127375edddedb1aa43ad023dec612bb4a04` Hash scope: Hash scope not separately documented; inspect source record Archive member: artifacts/brandes2023-pmc10484790.xml.gz Inspected artifact

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Sources and history

Release 2026-10-22-1b7cf027e4f6 · Record review: source checked

3 source records and release history

Brandes et al. 2023 Supplementary Table 2: full benchmark evaluations of ESM1b and all other methods · Original source · Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10)
Genome-wide prediction of disease variant effects with a deep protein language model (Brandes et al., Nature Genetics 2023) · Original source · Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10)
Brandes et al. 2023 Supplementary Information (Supplementary Table 1 and Methods) · Original source · Version of record, Nature Genetics 55, 1512-1522 (published 2023-08-10)

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Technical metadata and extraction receipts

Stable ID: gfm-guides-20261014-esm1b-data-clinvar-stop-gains-no-nmd

areas: dna-genomes; protein-function
contexts: clinical_research
split: Whole labelled set; no training on labels
subset scope: Stop-gain variants for which the 50 bp rule predicts no nonsense-mediated decay: 3,672 pathogenic and 147 benign.
source dataset label: ClinVar stop-gains
source locator: Supplementary Table 2 'Contents', column AUC_no_NMD; Fig. 6d legend; Methods 'AUC metrics for pathogenicity classification', paragraph on bootstrapping the stop-gain ROC-AUC
missing metadata: version: reason: inapplicable; note: Subset of the parent dataset
positive count: 3672
scored count: 3819

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