Paper Citation Record · LEDGER

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer

As of 22 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2608.09142.

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

pith.paper-citation-record.v1
2608.09142 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:44:26.544883Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact1
verified fuzzy14
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b5039ed6-3c53-4916-82a9-68ed0aadb843 · outbound

This paper cites reasoning.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer reasoning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:31.014745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 79875b4e-d0f1-4c6b-891b-1c83bc991698 · outbound

This paper cites forgetting issue.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer forgetting issue

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:30.882526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2144613a-cbab-4694-94cd-34f20c3d3e04 · outbound

This paper cites The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:30.574754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2c132ae0-faa4-4cae-a6df-7aa807b28a7b · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.064745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5904abe-b9b9-47e8-aef2-d56415aeda71 · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.301384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5b75f21-e48e-48ea-bd0f-52c21b32e2d3 · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer gpt-oss-120b & gpt-oss-20b Model Card

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.354751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2b04f7d-127b-4739-8944-56b49923da97 · outbound

This paper cites 14 Chen S, Kann BH, Foote MB, et al.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer 14 Chen S, Kann BH, Foote MB, et al

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:25.995573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67a5d541-b8fc-4211-a54b-0799b4016f39 · outbound

This paper cites 27 Asgari E, Montaña-Brown N, Dubois M, et al.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer 27 Asgari E, Montaña-Brown N, Dubois M, et al

Reference 10

Resolution: verified exact; doi, observed 2026-08-11T22:44:26.904847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7fe4db57-a914-4b29-80dc-1d22a5fe9913 · outbound

This paper cites MedGemma Technical Report.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer MedGemma Technical Report

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.114740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00d15081-2672-46d7-b625-780589e710e6 · outbound

This paper cites UniEval: Unified Holistic Evaluation for Unified Multimodal Understanding and Generation.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer UniEval: Unified Holistic Evaluation for Unified Multimodal Understanding and Generation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.519868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5830a07-be68-47e2-9ba0-7c134178ba0d · outbound

This paper cites Defining an evidence-based strategy for streamlining cancer multidisciplinary team meetings.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Defining an evidence-based strategy for streamlining cancer multidisciplinary team meetings

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:30.234754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e64b0c75-8d1a-481e-92a9-0b1a1afb429a · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Overcoming catastrophic forgetting in neural networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.222150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 276bd8e5-39f7-463e-889e-d1f4b17418cf · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer BERTScore: Evaluating Text Generation with BERT

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.454749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f338d3b-4f29-4c92-a8c5-a990be57a6fa · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.268024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47e0bcb8-ea0a-4100-98ec-b1d744447632 · outbound

This paper cites The Faiss library.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer The Faiss library

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.319586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daf1697f-52ab-423e-9816-b1ce2b25aea0 · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.259059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 145752df-c8a2-490c-869d-1c11730c6017 · outbound

This paper cites MEDITRON-70B: Scaling Medical Pretraining for Large Language Models.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer MEDITRON-70B: Scaling Medical Pretraining for Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.286415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68274fd0-cac8-4c7f-bb08-885397e5c6ff · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.404750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92246f0d-52f8-404b-b2df-b2fb9f8a1ba2 · outbound

This paper cites The Llama 3 Herd of Models.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer The Llama 3 Herd of Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.038615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0167362-1990-4514-bd85-5bafcd95d400 · outbound

This paper cites hallucinations.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer hallucinations

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:30.754751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b74c3160-c04a-42eb-a0fa-de7c1fc58438 · outbound

This paper cites Enhancing EHR-based pancreatic cancer prediction with LLM-derived embeddings.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Enhancing EHR-based pancreatic cancer prediction with LLM-derived embeddings

Reference 141

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:29.905072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bc2c9b50-600a-4f4e-be5c-b4677e98a305 · outbound

This paper cites ESMO guidance on the use of Large Language Models in Clinical Practice (ELCAP).

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer ESMO guidance on the use of Large Language Models in Clinical Practice (ELCAP)

Reference 274

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:29.074737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9dd6d0a4-fb2f-4940-b914-ca3531740ae6 · outbound

This paper cites Generative artificial intelligence to transform inpatient discharge summaries to patient-friendly language and format.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Generative artificial intelligence to transform inpatient discharge summaries to patient-friendly language and format

Reference 329

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:29.244748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 00e49410-58b8-42c5-87f5-cffd84b73415 · outbound

This paper cites Large language model influence on diagnostic reasoning: A randomized clinical trial.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Large language model influence on diagnostic reasoning: A randomized clinical trial

Reference 465

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:29.724751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4f99e64d-3140-4b46-b5d4-b8640b1456b8 · outbound

This paper cites Review of precision cancer medicine: Evolution of the treatment paradigm.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Review of precision cancer medicine: Evolution of the treatment paradigm

Reference 561

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:30.404750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 65d38efb-8ed4-4490-8d45-342964bfcca6 · outbound

This paper cites Evaluating large language models and agents in healthcare: key challenges in clinical applications.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Evaluating large language models and agents in healthcare: key challenges in clinical applications

Reference 600

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:28.884747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ed2285cb-e2c0-4f51-b64c-c791f5cc7df5 · outbound

This paper cites A large language model for electronic health records.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer A large language model for electronic health records

Reference 1032

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:30.074755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 55c10d60-c04a-42e6-82e0-720d50fb33f7 · outbound

This paper cites The quality and safety of using generative AI to produce patient-centred discharge instructions.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer The quality and safety of using generative AI to produce patient-centred discharge instructions

Reference 1932

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:29.405187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c2809b63-3885-4eba-8641-78c5b4345328 · outbound

This paper cites an unresolved cited work.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer Unresolved cited work

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.544883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 365896be-212c-4b47-9cd7-d26ed06aa001 · outbound

This paper cites 50 Zha Y, Yang Y, Li R, Hu Z.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer 50 Zha Y, Yang Y, Li R, Hu Z

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.476293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 972273f9-a9af-4218-9962-58efe8069a2b · outbound

This paper cites 51 Li Y, Wang H, Zhang Q, et al.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer 51 Li Y, Wang H, Zhang Q, et al

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T22:44:26.495854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 651bd1d8-2fcb-4465-89c3-4d62b97cbf2b · outbound

This paper cites The Llama 3 herd of models.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer The Llama 3 herd of models

Reference 9799

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:44:29.538379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.