This paper-specific evaluation tests antibody deamidation-site prediction using antibody peptide-mapping training dataset.
Explanatory profile: limited source coverage · Automated source review, 2026-09-16. This does not change the review status of its results.
| Property | Description and evidence |
|---|---|
| Record type | Paper-specific task; protocol incompletely extractedThe Accurate Prediction of Antibody Deamidations by Combining High-Throughput Automated Peptide Mapping and Protein Language Model-Based Deep Learning · Table 1, Global embeddings only row, Accuracy column |
| Inputs | antibody peptide-mapping training datasetThe Accurate Prediction of Antibody Deamidations by Combining High-Throughput Automated Peptide Mapping and Protein Language Model-Based Deep Learning · Table 1, Global embeddings only row, Accuracy column |
| Assessment | accuracyThe Accurate Prediction of Antibody Deamidations by Combining High-Throughput Automated Peptide Mapping and Protein Language Model-Based Deep Learning · Table 1, Global embeddings only row, Accuracy column |
| Recorded split or evaluation setting | fivefold stratified CVThe Accurate Prediction of Antibody Deamidations by Combining High-Throughput Automated Peptide Mapping and Protein Language Model-Based Deep Learning · Table 1, Global embeddings only row, Accuracy column |
| Datasets | Not extracted or verified for this record. |
| Organisms | Not extracted or verified for this record. |
| Assays | Not extracted or verified for this record. |
| Adaptation | Not extracted or verified for this record. |
| Baselines | Not extracted or verified for this record. |
Outline of the existing paper extraction. Split membership, fitting details and scorer implementation remain incompletely reviewed.
The existing paper extraction describes: global contextual embeddings only. This description is retained with the exact evaluation records; it is not a new protocol reconstruction.
The Accurate Prediction of Antibody Deamidations by Combining High-Throughput Automated Peptide Mapping and Protein Language Model-Based Deep Learning · Table 1, Global embeddings only row, Accuracy columnRelease 2026-09-16-d74d282221a9 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| ESM-2 650M embeddings + classifier: antibody deamidation-site prediction Model: ESM-2 650M embeddings + classifier · Benchmark: antibody deamidation-site prediction · Dataset: antibody peptide-mapping training dataset global contextual embeddings only Author-reported evaluation · Evaluation metadata: needs review | ||
| 0.944 accuracy Unit: fraction · Direction: unknown | Uncertainty: ± 0.012 Scored: Not reported · Eligible: Not reported | source checkedThe Accurate Prediction of Antibody Deamidations by Combining High-Throughput Automated Peptide Mapping and Protein Language Model-Based Deep Learning · Table 1, Global embeddings only row, Accuracy column Source checking is not independent reproduction. |
Catalogue extraction inspected; protocol claims remain limited to the cited evidence. Missing details are not presumed absent from the original paper.
Stable record: reported-task-0647b0364def8fRelease 2026-09-16-d74d282221a9 · Record review: needs review
Stable ID: reported-task-0647b0364def8f