Pith. sign in

Paper Citation Record · LEDGER

Self-aware and Cross-sample Prototypical Learning for Semi-supervised 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:2305.16214.

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

pith.paper-citation-record.v1
2305.16214 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:28:49.008978Z

measured 0 of 1 external citation measurements

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 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.

source=pdf_text observed=2026-08-07T15:28:49.008978Z digest=sha256:3c4528c7ca465adb6c2636aa3777833127fbe84ef349a1dcbb24b8d4dd766058

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-09T21:40:31.628704Z digest=sha256:02d51e1bc21969a9e3b264128f9b5aedfd6ea5e19c1e271cd0197e7b06d411b5