Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Overcoming Annotation Bottlenecks in Underwater Fish Segmentation: A Robust Self-Supervised Learning Approach
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2206.05390.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T18:35:53.491943Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-09T14:32:37.289205Z
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 2da83d94-1c01-4cec-9cb1-036c663e6a2d · inbound
Advancing Oyster Phenotype Segmentation with Multi-Network Ensemble and Multi-Scale mechanism cites this paper.
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.
Observation bf59f670-0f08-411c-aaff-d07bae9af006 · inbound
AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis cites this paper.
AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis Overcoming Annotation Bottlenecks in Underwater Fish Segmentation: A Robust Self-Supervised Learning Approach
Reference 101
- Resolution
- verified exact
- local_arxiv, observed 2026-08-09T14:32:37.293130Z
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.