Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image Segmentation
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.16214.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T17:33:05.009864Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-09T21:46:34.609299Z
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 cc01ae18-be28-47a8-8bc6-e0676a391c5c · inbound
A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation cites this paper.
A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image Segmentation
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T17:33:05.009864Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fab37e5d-2689-45c7-9047-132976b53575 · inbound
P3Net: Progressive and Periodic Perturbation for Semi-Supervised Medical Image Segmentation cites this paper.
P3Net: Progressive and Periodic Perturbation for Semi-Supervised Medical Image Segmentation Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image Segmentation
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:28:49.008978Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 815c9cd4-7db4-4b19-aae7-7f89aa23b1ca · inbound
SHTA: Semantic Hard Token Correction and Center Alignment for Semi-Supervised Medical Image Segmentation cites this paper.
SHTA: Semantic Hard Token Correction and Center Alignment for Semi-Supervised Medical Image Segmentation Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image Segmentation
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T21:46:34.611080Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.