Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
De-identification is not enough: a comparison between de-identified and synthetic clinical notes
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.00179.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:37:05.336935Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T19:41:14.020069Z
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 1b4d3ca9-33c8-46f5-b3f0-300667ceb251 · inbound
Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions cites this paper.
Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions De-identification is not enough: a comparison between de-identified and synthetic clinical notes
Reference 251
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:37:05.336935Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fdd80fe5-cb7c-47ea-8976-77bc9fb738f4 · inbound
Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies cites this paper.
Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies De-identification is not enough: a comparison between de-identified and synthetic clinical notes
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T19:41:14.025739Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.