Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data
Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 · Preprint
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- scBERT: description: Description Transformer model, pretrained on unlabelled single-cell RNA-seq data in the manner of BERT, that is fine-tuned to annotate cell types. (qa-descriptions-20261011-b-source-scbert: abstractText; coverage-source-scfoundation-supp: Supplementary Table 4)
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Pipelines (1)
Evidence
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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.
26 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.artifact_sha256 0a1fd6b679260955dc4382dd73b4f94f51fcf575ce0915d011913db425e99dff Source metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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. |
| Artifact url https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=TITLE%3A%22scBERT%20as%20a%20large-scale%20pretrained%20deep%20language%20model%22&format=json&resultType=core Source metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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. |
| 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 metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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. |
| Media type application/json Source metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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. |
| Missing metadata: licence: note The retrieved record or document gives no licence Source metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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. |
| Missing metadata: licence: reason unreported Source metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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. |
| Publication status preprint Source metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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. |
| Retrieved at 2026-10-11T00:59:14Z Source metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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. |
| Review: date 2026-10-11 Source metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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. |
| Review: 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. Source metadata | Abstract: scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data No field-specific location recorded Version: Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021 | catalogued 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
Source text retrieved and hashed for the issue #88 placeholder-description fix.
Technical metadata and extraction receipts
Stable ID: qa-descriptions-20261011-b-source-scbert
- url
- https://doi.org/10.1101/2021.12.05.471261
- artifact url
- https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=TITLE%3A%22scBERT%20as%20a%20large-scale%20pretrained%20deep%20language%20model%22&format=json&resultType=core
- version
- Europe PMC preprint record PPR/PPR428747 (title and abstract), bioRxiv 2021
- retrieved at
- 2026-10-11T00:59:14Z
- artifact sha256
- 0a1fd6b679260955dc4382dd73b4f94f51fcf575ce0915d011913db425e99dff
- publication status
- preprint
- media type
- application/json
- source locator
- abstractText
- 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.
- missing metadata
- licence: reason: unreported; note: The retrieved record or document gives no licence
- 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 new sources' licences against the arXiv abstract pages and Europe PMC, the 7 scFoundation pipeline descriptions against their abstracts, the language-model descriptions against their model cards and reports, and the TAPE architecture figures against the TAPE paper; all correct. The catalogue entries reuse reviewed profile summaries.; receipt: data/omics/qa-descriptions-20261011-b/review.json; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=TITLE%3A%22scBERT%20as%20a%20large-scale%20pretrained%20deep%20language%20model%22&format=json&resultType=core