Strengths and considerations
No source-reviewed explanatory claims are recorded here yet.
model · method
ESM-2 650M embeddings + classifier
ESM-2 650M embeddings + classifier is the method recorded for antibody deamidation-site prediction. This page preserves the configuration reported by The Accurate Prediction of Antibody Deamidations by Combining High-Throughput Automated Peptide Mapping and Protein Language Model-Based Deep Learning.
At a glance
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 |
|---|---|
| Recorded dataset | 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 |
| Recorded split | 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 |
| Recorded configuration | esm2_t33_650m_UR50DThe 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 |
| Model type | Not extracted or verified for this record. |
| Training data | Not extracted or verified for this record. |
| Context limits | Not extracted or verified for this record. |
| Access | Not extracted or verified for this record. |
| Code licence | Not extracted or verified for this record. |
| Weights licence | Not extracted or verified for this record. |
How it works
Recorded evaluation
The imported evaluation describes this procedure: global contextual embeddings only
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 columnBenchmarks and results
Release 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. |
Strengths and limitations
Limitations and conditions
- This is an evidence-limited profile. The recorded evaluation context does not establish performance on other datasets or configurations.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 column
Profile review details
Reviewed the existing release record, its source pointer and linked evaluation context. This is not a fresh full-text architecture review or independent reproduction; numerical review status is unchanged.
Stable record: reported-model-4921459942b45fSources and history
Release 2026-09-16-d74d282221a9 · Record review: needs review
- The Accurate Prediction of Antibody Deamidations by Combining High-Throughput Automated Peptide Mapping and Protein Language Model-Based Deep Learning · Original source · journal full text in PMC
Technical metadata and extraction receipts
Stable ID: reported-model-4921459942b45f
- areas
- proteins-complexes
- entity level
- method
- version
- esm2_t33_650m_UR50D
- reported name
- ESM-2 650M embeddings + classifier
- missing metadata
- checkpoint revision: not_reported_in_legacy_extract; training data: not_reported_in_legacy_extract; licence: not_reported_in_legacy_extract