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Paper Citation Record · LEDGER

Predicting Early-Onset Colorectal Cancer with Large Language Models

As of 11 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 1 inbound Pith citation observation for arXiv:2506.11410.

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

pith.paper-citation-record.v1
2506.11410 v1

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:15:11.338949Z

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:42:25.560175Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

2 of 2 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 8564c391-53ed-43db-a0a2-6b71631fd33f · outbound

This paper cites Advanced-stage colorectal cancer in persons younger than 50 years not associated with longer dura.on of symptoms or .me to diagnosis.

Predicting Early-Onset Colorectal Cancer with Large Language Models Advanced-stage colorectal cancer in persons younger than 50 years not associated with longer dura.on of symptoms or .me to diagnosis

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:15:11.492161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:15:11.279460Z digest=sha256:671e36de2d10197ca355b53ae636c73f69ca452bf2f70ae96f8dfcc49c420034

Observation 71f06a7b-766f-4139-80f5-ef3a15100d30 · outbound

This paper cites Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale.

Predicting Early-Onset Colorectal Cancer with Large Language Models Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T04:15:11.338949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:11.338949Z digest=sha256:f17bb342022b27039934677837998c53e09b93b6b01b01011695ed9135bfe363

Pith citing papers

Observation 400bbe45-8682-4fef-8977-3bb45a4d0ef5 · inbound

TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection cites this paper.

TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection Predicting Early-Onset Colorectal Cancer with Large Language Models

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-10T16:45:36.688226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T16:42:25.560175Z digest=sha256:662180b6553096f60d8b383b96e20847ee3108f7013485d8e07380f26996e4a9