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Paper Citation Record · LEDGER

SAM3D: Segment Anything Model in Volumetric Medical Images

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2309.03493.

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

pith.paper-citation-record.v1
2309.03493 v4

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:20:58.594473Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-09T11:21:46.018214Z

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 37df8d51-fff2-4bfc-9c62-26030cf3c601 · inbound

Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation cites this paper.

Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation SAM3D: Segment Anything Model in Volumetric Medical Images

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T18:20:58.594473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:20:58.594473Z digest=sha256:ffacbab31c5e8d413acad731ee2d61aa3dba3a3788f6b2c9382d353f39e4ca6e

Observation 9adb8d88-9c83-4631-bc2a-88e2a389bcbc · inbound

RFMedSAM 2: Automatic Prompt Refinement for Enhanced Volumetric Medical Image Segmentation with SAM 2 cites this paper.

RFMedSAM 2: Automatic Prompt Refinement for Enhanced Volumetric Medical Image Segmentation with SAM 2 SAM3D: Segment Anything Model in Volumetric Medical Images

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-09T11:21:46.024808Z

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.

source=pdf_text observed=2026-08-09T11:21:45.725485Z digest=sha256:f1efe6b9648330ad765e68ddcac27e6252cbc1fe79dba8c09fd3f7be3062cb0f