Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
CU-Net: a U-Net architecture for efficient brain-tumor segmentation on BraTS 2019 dataset
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.13113.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T17:19:45.499425Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T21:57:28.700525Z
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 6624450d-d62d-47b1-bbdc-9ad2e3f8f74a · inbound
IoT-Based 3D Pose Estimation and Motion Optimization for Athletes: Application of C3D and OpenPose cites this paper.
IoT-Based 3D Pose Estimation and Motion Optimization for Athletes: Application of C3D and OpenPose CU-Net: a U-Net architecture for efficient brain-tumor segmentation on BraTS 2019 dataset
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T17:19:45.499425Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f6d6c531-4181-4bfb-84b6-4889341c631d · inbound
Optimized CNNs for Rapid 3D Point Cloud Object Recognition cites this paper.
Optimized CNNs for Rapid 3D Point Cloud Object Recognition CU-Net: a U-Net architecture for efficient brain-tumor segmentation on BraTS 2019 dataset
Reference 88
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T23:06:27.839849Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6dedb7ac-d90e-42ed-a277-adcd2c5628ac · inbound
Electronic Health Records-Based Data-Driven Diabetes Knowledge Unveiling and Risk Prognosis cites this paper.
Electronic Health Records-Based Data-Driven Diabetes Knowledge Unveiling and Risk Prognosis CU-Net: a U-Net architecture for efficient brain-tumor segmentation on BraTS 2019 dataset
Reference 86
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T21:57:28.703419Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.