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Paper Citation Record · LEDGER

A new paradigm for accelerating clinical data science at Stanford Medicine

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2003.10534.

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

pith.paper-citation-record.v1
2003.10534 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:39:55.612867Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T00:17:28.522483Z

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 4ea49026-2b4a-4cba-9d7d-411f9bb7717d · inbound

Compliant Self Service Access to Secondary Use Clinical Data at Stanford Medicine cites this paper.

Compliant Self Service Access to Secondary Use Clinical Data at Stanford Medicine A new paradigm for accelerating clinical data science at Stanford Medicine

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T21:39:55.612867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:55.612867Z digest=sha256:bd3ed61ff16db1aaadbede69c698560024ea12e95b84e40e5bfd100996d3f724

Observation dab33dfd-8b8c-410c-9b7d-949c529df2c8 · inbound

MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents cites this paper.

MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents A new paradigm for accelerating clinical data science at Stanford Medicine

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T14:58:40.199697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:58:40.199697Z digest=sha256:de1a35f8db4a88cc50c7a940c839982cb2a2363f8955a5699c03de6112b4fb21

Observation d36f8906-a6a8-474c-9f4d-5e15dc5911fb · inbound

PhysicianBench: Evaluating LLM Agents in Real-World EHR Environments cites this paper.

PhysicianBench: Evaluating LLM Agents in Real-World EHR Environments A new paradigm for accelerating clinical data science at Stanford Medicine

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:31:06.488404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-09T16:36:39.233362Z digest=sha256:6244d94121f0bc519c4a3df984451db814bdb6b402fe1bd096bcb8da1260db23

Observation dfbdfb03-542a-49d3-b96d-b39c5d6d7db7 · 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 A new paradigm for accelerating clinical data science at Stanford Medicine

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:31:15.157496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-07T16:54:09.808284Z digest=sha256:23556413a09e7d4cc5e0b56d42711fe6205c72ed5e18532e379915d47f04e985

Observation d177abe6-8267-4d08-bf45-b26a0220c87f · 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 A new paradigm for accelerating clinical data science at Stanford Medicine

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:17:28.525265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-07-03T00:10:39.112280Z digest=sha256:6be92b7dfc0eb342f86be822174cced1ee087b24e1c79f5b1ba8ff2307a99beb