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Paper Citation Record · LEDGER

A Probabilistic U-Net for Segmentation of Ambiguous Images

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1806.05034.

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

pith.paper-citation-record.v1
1806.05034 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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:18:30.087654Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T14:18:31.066965Z

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 13253633-7285-4cf4-b1d5-e2e60105deb8 · inbound

SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation cites this paper.

SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation A Probabilistic U-Net for Segmentation of Ambiguous Images

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-12T14:18:31.106565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:18:30.087654Z digest=sha256:03b82b507fecafc04602a6a8bdf6041237ea018ee2cb55ee15ba9774dd09032c

Observation a3ad3fed-be01-409c-aec8-8bafc72c0ae9 · inbound

Incomplete Observations Boost Evolutionary Performance in Ocean Modeling cites this paper.

Incomplete Observations Boost Evolutionary Performance in Ocean Modeling A Probabilistic U-Net for Segmentation of Ambiguous Images

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-01T13:22:15.451562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T13:22:15.451562Z digest=sha256:a8592d5c77d413934f05f588a0c17bc828e9ca5147721cd7a97b88fed35a4104