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Paper Citation Record · LEDGER

Advancing Oyster Phenotype Segmentation with Multi-Network Ensemble and Multi-Scale mechanism

As of 11 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 0 inbound Pith citation observations for arXiv:2501.11203.

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

pith.paper-citation-record.v1
2501.11203 v1

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:35:53.491943Z

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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

2 of 2 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2da83d94-1c01-4cec-9cb1-036c663e6a2d · outbound

This paper cites Overcoming Annotation Bottlenecks in Underwater Fish Segmentation: A Robust Self-Supervised Learning Approach.

Advancing Oyster Phenotype Segmentation with Multi-Network Ensemble and Multi-Scale mechanism Overcoming Annotation Bottlenecks in Underwater Fish Segmentation: A Robust Self-Supervised Learning Approach

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-10T18:35:53.491943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:35:53.491943Z digest=sha256:e563897a1207d2254d744d6478d9bcf97f9af59fa3776c8da92c391849134b6d

Observation acf6ed4a-7a60-42ac-8462-1e3edce3a303 · outbound

This paper cites CellViT: Vision Transformers for Precise Cell Segmentation and Classification.

Advancing Oyster Phenotype Segmentation with Multi-Network Ensemble and Multi-Scale mechanism CellViT: Vision Transformers for Precise Cell Segmentation and Classification

Reference 2017

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:35:53.539715Z

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=2026-08-10T18:35:53.486958Z digest=sha256:9120b96601bdf297348f698dcfd4cb181e1af236e465daa18b2de8c41be74b14

Pith citing papers

No inbound Pith citation observations are available.