Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2308.06294.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T04:04:13.357571Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T03:57:02.922104Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 642096c1-9285-44d2-af69-39a3afc7d841 · inbound
RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Records cites this paper.
RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Records Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-07-15T00:21:10.130997Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0739b984-f5f5-4397-b445-cf477b440867 · inbound
Toward Automated Detection of Documentation Inconsistencies in Electronic Health Records cites this paper.
Toward Automated Detection of Documentation Inconsistencies in Electronic Health Records Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T04:04:13.357571Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.