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Paper Citation Record · LEDGER

VIBESegmentator: Full Body MRI Segmentation for the NAKO and UK Biobank

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.00125.

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

pith.paper-citation-record.v1
2406.00125 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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:41:56.919932Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 43318a0f-1e9f-4efd-baad-81bea275e0ce · inbound

Benchmarking of Deep Learning Methods for Generic MRI Multi-Organ Abdominal Segmentation cites this paper.

Benchmarking of Deep Learning Methods for Generic MRI Multi-Organ Abdominal Segmentation VIBESegmentator: Full Body MRI Segmentation for the NAKO and UK Biobank

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T14:41:56.919932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:41:56.919932Z digest=sha256:3e02b2c3c6f38cb196deaa53d21753c16b6991383ffd84ff23368699cb9e73df

Observation 500e4927-19ef-4b31-9e65-903b5e0a702a · inbound

In search of truth: Evaluating concordance of AI-based anatomy segmentation models cites this paper.

In search of truth: Evaluating concordance of AI-based anatomy segmentation models VIBESegmentator: Full Body MRI Segmentation for the NAKO and UK Biobank

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:08:32.436527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T21:04:17.071422Z digest=sha256:03f9a87a655f14042e0c6f8feea5051e44632cdf995359bfe2f99d136e819f4c