Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2505.10502.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-18T20:22:41.555806Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T20:22:50.716750Z
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 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 2026-08-06T06:34:29.942622+00:00.