Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.05506.
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 2026-08-07T15:29:05.026476Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z
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 f556a6e8-17ee-4aab-8096-c8549633b3bb · inbound
Diagnosing our datasets: How does my language model learn clinical information? cites this paper.
Diagnosing our datasets: How does my language model learn clinical information? Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:29:05.026476Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a80e5e0-0d68-44dc-bad7-a3858afcc7ab · inbound
Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models cites this paper.
Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
Reference 3414
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T23:19:54.397599Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b836934e-0727-4a69-9d3f-467bd61d10cd · inbound
Surrogate modeling for interpreting black-box LLMs in medical predictions cites this paper.
Surrogate modeling for interpreting black-box LLMs in medical predictions Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T00:34:47.178252Z
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.