Paper Citation Record · LEDGER

Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2405.05506.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2405.05506 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T13:58:44.440646Z

measured 0 of 1 external citation measurements

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 78b960c2-38b4-41ba-8ca5-ad4648c0f6c4 · inbound

Regulatory Science Innovation for Generative AI and Large Language Models in Health and Medicine: A Global Call for Action cites this paper.

Regulatory Science Innovation for Generative AI and Large Language Models in Health and Medicine: A Global Call for Action Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-10T13:58:44.440646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-17T06:30:58.91139+00:00.