Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Validating transformers for redaction of text from electronic health records in real-world healthcare
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.04468.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-03T00:10:39.112280Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T00:17:28.529793Z
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 2d379066-a2fd-4714-96bb-6917e700b135 · inbound
SHIELD: A Diverse Clinical Note Dataset and Distilled Small Language Models for Enterprise-Scale De-identification cites this paper.
SHIELD: A Diverse Clinical Note Dataset and Distilled Small Language Models for Enterprise-Scale De-identification Validating transformers for redaction of text from electronic health records in real-world healthcare
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T23:31:15.170242Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 266dedaa-2244-4896-9fe4-2630137eb7d8 · inbound
SHIELD: A Diverse Clinical Note Dataset and Distilled Small Language Models for Enterprise-Scale De-identification cites this paper.
SHIELD: A Diverse Clinical Note Dataset and Distilled Small Language Models for Enterprise-Scale De-identification Validating transformers for redaction of text from electronic health records in real-world healthcare
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:28.531416Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.