Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Convolutional neural networks for medical image segmentation
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.09562.
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 2026-08-06T05:16:40.549324Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T20:47:22.574782Z
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 7047fd0c-e65c-4cc2-aa67-021d12da16a4 · inbound
Hybrid Compact Least-Squares and Central Weighted Essentially Non-Oscillatory Schemes for Hyperbolic Conservation Laws on Structured Curvilinear Grids cites this paper.
Hybrid Compact Least-Squares and Central Weighted Essentially Non-Oscillatory Schemes for Hyperbolic Conservation Laws on Structured Curvilinear Grids Convolutional neural networks for medical image segmentation
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:16:40.549324Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d5781161-08d1-4287-a5de-f42826c7cfab · inbound
Multi-planar 2D-U-Net Segmentation of 3D-CT Abdominal Organs augmented by Spatial Occurrence Maps cites this paper.
Multi-planar 2D-U-Net Segmentation of 3D-CT Abdominal Organs augmented by Spatial Occurrence Maps Convolutional neural networks for medical image segmentation
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T20:47:22.576481Z
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.