ABYSSAL: description
Description of ABYSSAL
ESM-2 network with an added light-attention mechanism, trained on the mega-scale stability dataset, which predicts the stability change on single mutation and satisfies the antisymmetry property.
Replace a category-only description with a sourced functional description (issue #88). Historical releases retain the original value.
Evidence
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
Evidence table
Inspect claims, sources and review details
Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.
One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
7 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Claimed field description Context-only references | Abstract: New mega dataset combined with deep neural network makes a progress in predicting impact of mutation on protein stability (ABYSSAL) qa-descriptions-20261011-d-source-abyssal: abstractText Version: Europe PMC preprint record PPR/PPR590902 (title and abstract), bioRxiv 2023 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a Europe PMC REST search response. These responses are not byte-stable (a later retrieval can differ in JSON key order); the title and abstractText fields are the evidence. |
| Previous value Protein stability-change (ddG) predictor. Context-only references | Abstract: New mega dataset combined with deep neural network makes a progress in predicting impact of mutation on protein stability (ABYSSAL) qa-descriptions-20261011-d-source-abyssal: abstractText Version: Europe PMC preprint record PPR/PPR590902 (title and abstract), bioRxiv 2023 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a Europe PMC REST search response. These responses are not byte-stable (a later retrieval can differ in JSON key order); the title and abstractText fields are the evidence. |
| Source location qa-descriptions-20261011-d-source-abyssal: abstractText Context-only references | Abstract: New mega dataset combined with deep neural network makes a progress in predicting impact of mutation on protein stability (ABYSSAL) qa-descriptions-20261011-d-source-abyssal: abstractText Version: Europe PMC preprint record PPR/PPR590902 (title and abstract), bioRxiv 2023 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a Europe PMC REST search response. These responses are not byte-stable (a later retrieval can differ in JSON key order); the title and abstractText fields are the evidence. |
| Claimed value ESM-2 network with an added light-attention mechanism, trained on the mega-scale stability dataset, which predicts the stability change on single mutation and satisfies the antisymmetry property. Context-only references | Abstract: New mega dataset combined with deep neural network makes a progress in predicting impact of mutation on protein stability (ABYSSAL) qa-descriptions-20261011-d-source-abyssal: abstractText Version: Europe PMC preprint record PPR/PPR590902 (title and abstract), bioRxiv 2023 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a Europe PMC REST search response. These responses are not byte-stable (a later retrieval can differ in JSON key order); the title and abstractText fields are the evidence. |
| Description Replace a category-only description with a sourced functional description (issue #88). Historical releases retain the original value. Context-only references | Abstract: New mega dataset combined with deep neural network makes a progress in predicting impact of mutation on protein stability (ABYSSAL) qa-descriptions-20261011-d-source-abyssal: abstractText Version: Europe PMC preprint record PPR/PPR590902 (title and abstract), bioRxiv 2023 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a Europe PMC REST search response. These responses are not byte-stable (a later retrieval can differ in JSON key order); the title and abstractText fields are the evidence. |
| Relationship: subject protein-stability-20261009-method-abyssal Context-only references | Abstract: New mega dataset combined with deep neural network makes a progress in predicting impact of mutation on protein stability (ABYSSAL) qa-descriptions-20261011-d-source-abyssal: abstractText Version: Europe PMC preprint record PPR/PPR590902 (title and abstract), bioRxiv 2023 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a Europe PMC REST search response. These responses are not byte-stable (a later retrieval can differ in JSON key order); the title and abstractText fields are the evidence. |
| Name ABYSSAL: description Context-only references | Abstract: New mega dataset combined with deep neural network makes a progress in predicting impact of mutation on protein stability (ABYSSAL) qa-descriptions-20261011-d-source-abyssal: abstractText Version: Europe PMC preprint record PPR/PPR590902 (title and abstract), bioRxiv 2023 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a Europe PMC REST search response. These responses are not byte-stable (a later retrieval can differ in JSON key order); the title and abstractText fields are the evidence. |
Sources and history
Release 2026-10-22-1b7cf027e4f6 · Record review: source checked
1 source record and release history
- Abstract: New mega dataset combined with deep neural network makes a progress in predicting impact of mutation on protein stability (ABYSSAL) · Original source · Europe PMC preprint record PPR/PPR590902 (title and abstract), bioRxiv 2023
Technical metadata and extraction receipts
Stable ID: metadata-correction-f6f3db11f0ddfbca9b96
- areas
- proteins-complexes
- contexts
- research
- method types
- supervised_machine_learning
- field
- description
- previous value
- Protein stability-change (ddG) predictor.
- value
- ESM-2 network with an added light-attention mechanism, trained on the mega-scale stability dataset, which predicts the stability change on single mutation and satisfies the antisymmetry property.
- source locator
- qa-descriptions-20261011-d-source-abyssal: abstractText
- review
- method: automated-source-review; ai-assisted-source-review; reviewer: claude; reviewer note: Extractor: Claude integrator agent for issue #88. Reviewer: a separate Claude review agent, independent of the extractor; no human review claimed.; date: 2026-10-11; method note: Compared the store diff with origin/main, read each new description against its cited source passage and checked the licence of each new source record.; note: Approved. Checked the 16 Pancotti-derived descriptions word for word against PMC8921618 section 2.2, ESM therm, RaSP and ELASPIC-2 against Chu 2024, ThermoMPNN against Dieckhaus 2024, and ABYSSAL and phyloP against their abstracts; all match. Licences on the new sources are supported by Europe PMC, the PMC XML and Crossref.; receipt: data/omics/qa-descriptions-20261011-d/review.json
Related records
- subject: ABYSSAL