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scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Primary paper retained with its original identifier. Metadata inherited from the literature collection; individual result checks are separate.

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.

28 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-29-06401fd5b220
Property and statementOriginal source and locationReview and provenance
attributes.artifact_retrieved_at
2026-09-16T10:33:50.056Z
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.artifact_retrieved_at

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

attributes.artifact_sha256
47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.artifact_sha256

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

attributes.artifact_url
https://www.ebi.ac.uk/europepmc/webservices/rest/PMC12859067/fullTextXML
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.artifact_url

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

attributes.doi
10.1038/s42003-025-09418-5
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.doi

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

attributes.legacy_paper.doi
10.1038/s42003-025-09418-5
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.legacy_paper.doi

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

attributes.legacy_paper.id
scxdr-2026
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.legacy_paper.id

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

attributes.legacy_paper.notes
Primary full text verified using Europe PMC XML; venue: Communications Biology; PMC ID: PMC12859067.
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.legacy_paper.notes

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

attributes.legacy_paper.primary_domain
cells-tissues
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.legacy_paper.primary_domain

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

attributes.legacy_paper.publication_status
peer_reviewed
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.legacy_paper.publication_status

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

attributes.legacy_paper.retrieved_utc
2026-09-15T23:29:32Z
Source metadata
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning

Original source ↗

No field-specific location recorded

Version: PMC archival version PMC12859067.1
Retrieved: 2026-09-16T10:33:50.056Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.legacy_paper.retrieved_utc

Source artifact SHA-256: 47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Sources and history

View linked audit checks and correction history

Release 2026-09-29-06401fd5b220 · Record review: discovered

0 source records and release history

No supporting source is linked yet.

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Technical metadata and extraction receipts

Stable ID: scxdr-2026

areas
cells-tissues
url
https://pmc.ncbi.nlm.nih.gov/articles/PMC12859067/
version
PMC archival version PMC12859067.1
retrieved at
2026-09-15T23:29:32Z
doi
10.1038/s42003-025-09418-5
publication status
peer_reviewed
year
2026
artifact sha256
47b5925e9887d87fc8288d29288802b1d67d54f064d913151df92171f7c68d33
artifact url
https://www.ebi.ac.uk/europepmc/webservices/rest/PMC12859067/fullTextXML
artifact retrieved at
2026-09-16T10:33:50.056Z
legacy paper
id: scxdr-2026; title: scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning; year: 2026; publication status: peer_reviewed; version: PMC archival version PMC12859067.1; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC12859067/; primary domain: cells-tissues; retrieved utc: 2026-09-15T23:29:32Z; notes: Primary full text verified using Europe PMC XML; venue: Communications Biology; PMC ID: PMC12859067.; doi: 10.1038/s42003-025-09418-5
scope decision
included
missing metadata
licence: not_reported_in_legacy_extract
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