Paper Citation Record · LEDGER

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer

As of 19 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 4 inbound Pith citation observations for arXiv:2505.10502.

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

pith.paper-citation-record.v1
2505.10502 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:12:01.159326Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:37:02.112005Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T20:22:50.716750Z

Reference resolution

22 of 22 outbound references displayed

verified exact0
verified fuzzy12
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bd12b287-7f90-433e-9ddf-34c5ee4a0584 · outbound

This paper cites Rectal cancer: Esmo clinical practice guidelines for diagnosis, treatment and follow-up.Annals of On- cology, 28:iv22–iv40, 2017.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Rectal cancer: Esmo clinical practice guidelines for diagnosis, treatment and follow-up.Annals of On- cology, 28:iv22–iv40, 2017

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.470532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7dfcbdb8-2b2c-4e92-b332-ff4d626dfd1d · outbound

This paper cites an unresolved cited work.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:12:01.456874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b52741f1-bd68-4fba-bc6a-d73a72d3656a · outbound

This paper cites Deep submucosal invasion is not an independent risk factor for lymph node metastasis in t1 colorectal cancer: a meta-analysis.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Deep submucosal invasion is not an independent risk factor for lymph node metastasis in t1 colorectal cancer: a meta-analysis

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.443515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 80115dbf-7483-4699-8736-a1733161aba5 · outbound

This paper cites an unresolved cited work.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:12:01.429717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b27b6bf2-c235-45a8-bec4-0fc78bfe3688 · outbound

This paper cites Mri for evalua- tion of treatment response in rectal cancer.The British journal of radiology, 89(1064):20150964, 2016.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Mri for evalua- tion of treatment response in rectal cancer.The British journal of radiology, 89(1064):20150964, 2016

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.415078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7bfc23f1-a7c4-4517-8376-17c8176fe6a5 · outbound

This paper cites Mri of rectal cancer: tumor staging, imaging tech- niques, and management.Radiographics, 39(2):367–387, 2019.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Mri of rectal cancer: tumor staging, imaging tech- niques, and management.Radiographics, 39(2):367–387, 2019

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.399742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 62fafabc-f93f-4c81-abae-9dfc820b3046 · outbound

This paper cites Clinical lymph node staging in colorectal cancer; a flip of the coin?European Journal of Surgical Oncology, 44(8):1241–1246, 2018.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Clinical lymph node staging in colorectal cancer; a flip of the coin?European Journal of Surgical Oncology, 44(8):1241–1246, 2018

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.385351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bea0c877-736b-4456-bc5a-88bf215c02d1 · outbound

This paper cites Accuracy of various lymph node staging criteria in rectal cancer with magnetic resonance imaging.Journal of Gastrointestinal Surgery, 22:146–153, 2018.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Accuracy of various lymph node staging criteria in rectal cancer with magnetic resonance imaging.Journal of Gastrointestinal Surgery, 22:146–153, 2018

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.370969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 98976551-5d3c-4fd4-91c2-9cbe1d78bc89 · outbound

This paper cites Transmed: Transformers advance multi-modal medical image classification.Diagnostics, 11(8):1384, 2021.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Transmed: Transformers advance multi-modal medical image classification.Diagnostics, 11(8):1384, 2021

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.356894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6937a872-4122-47bb-a0a1-63ce5ad3c8ce · outbound

This paper cites An anatomy-aware framework for automatic segmentation of parotid tumor from multimodal mri.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer An anatomy-aware framework for automatic segmentation of parotid tumor from multimodal mri

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.341374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 55e8c708-09e5-4ab7-9f6d-8d93c03bf4f6 · outbound

This paper cites Desam: Decoupled segment anything model for generalizable medical image segmentation.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Desam: Decoupled segment anything model for generalizable medical image segmentation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T21:12:01.107326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecaaef6d-6663-4f2b-b00c-b769da95bd9d · outbound

This paper cites Mba-net: Sam-driven bidirec- tional aggregation network for ovarian tumor segmentation.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Mba-net: Sam-driven bidirec- tional aggregation network for ovarian tumor segmentation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T21:12:01.111765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6068b01-40bb-4e08-ba18-7f2c915a42c4 · outbound

This paper cites Sagl: A self-attention-based graph learning framework for predicting survival of colorectal cancer patients.Computer Methods and Programs in Biomedicine, 249:108159, 2024.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Sagl: A self-attention-based graph learning framework for predicting survival of colorectal cancer patients.Computer Methods and Programs in Biomedicine, 249:108159, 2024

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.306970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9966b625-6383-4c17-bf50-ee1581ac14b6 · outbound

This paper cites High-resolution mri-based radiomics analysis to predict lymph node metastasis and tumor deposits respectively in rectal cancer.Abdominal Radiology, 46:873–884, 2021.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer High-resolution mri-based radiomics analysis to predict lymph node metastasis and tumor deposits respectively in rectal cancer.Abdominal Radiology, 46:873–884, 2021

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.290695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2b59aea6-ea64-41ee-a656-d3a9d1683934 · outbound

This paper cites Artificial intelligence system to determine risk of t1 colorectal cancer metas- tasis to lymph node.Gastroenterology, 160(4):1075–1084, 2021.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Artificial intelligence system to determine risk of t1 colorectal cancer metas- tasis to lymph node.Gastroenterology, 160(4):1075–1084, 2021

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.276156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b172bb7c-f8c0-4c31-8621-a8f897c5e7e2 · outbound

This paper cites an unresolved cited work.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:12:01.262728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bb612d2f-97be-4a8f-9b4d-4859b5d8719b · outbound

This paper cites Multicenter evalua- tion of a weakly supervised deep learning model for lymph node diagnosis in rectal cancer at mri.Radiology: Artificial Intelligence, 6(2):e230152, 2024.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Multicenter evalua- tion of a weakly supervised deep learning model for lymph node diagnosis in rectal cancer at mri.Radiology: Artificial Intelligence, 6(2):e230152, 2024

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:12:01.249006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 554d2680-2ad6-41d9-a72e-0cc088d72876 · outbound

This paper cites an unresolved cited work.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:12:01.233886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fe2ce6a2-a0c4-4c08-8ae3-18e55b613e45 · outbound

This paper cites Searching for mobilenetv3.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Searching for mobilenetv3

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T21:12:01.144254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d727ca8a-78af-4773-b401-9f53ca499c08 · outbound

This paper cites Convnext v2: Co-designing and scaling convnets with masked autoencoders.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Convnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T21:12:01.148853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0da9ad64-5759-47de-921b-3524b4b9e288 · outbound

This paper cites Deep residual learning for image recognition.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Deep residual learning for image recognition

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T21:12:01.153758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28dff0ca-f5b3-4ffb-be96-e346951a4456 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer Swin transformer: Hierarchical vision transformer using shifted windows

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T21:12:01.159326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 0e7a1b6c-f40a-4c50-ae55-2d9404184e17 · inbound

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation cites this paper.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T11:37:02.112005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a121c0f3-478a-4c4f-bee6-2c1d7d6d9c2a · inbound

SafeClick: Error-Tolerant Interactive Segmentation of Any Medical Volumes via Hierarchical Expert Consensus cites this paper.

SafeClick: Error-Tolerant Interactive Segmentation of Any Medical Volumes via Hierarchical Expert Consensus WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T23:21:36.376443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10c57b1b-5fc2-476f-a60e-4504b9ef00c5 · inbound

LRMR: LLM-Driven Relational Multi-node Ranking for Lymph Node Metastasis Assessment in Rectal Cancer cites this paper.

LRMR: LLM-Driven Relational Multi-node Ranking for Lymph Node Metastasis Assessment in Rectal Cancer WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T17:15:41.305982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d1f260d-b160-4f90-92bf-5bb9e729521a · inbound

Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation cites this paper.

Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-18T20:22:50.720022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.