Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Leveraging Uncertainty Estimates for Predicting Segmentation Quality
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1807.00502.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T05:38:16.008468Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-01T22:06:16.682028Z
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 1a45cb50-5bca-41de-a42b-60b7a37e7c70 · inbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation cites this paper.
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Leveraging Uncertainty Estimates for Predicting Segmentation Quality
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:38:16.008468Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b7034f33-4466-4a07-a7b3-d6c173d0dc44 · inbound
Quality-Guided Semi-Supervised Learning for Medical Image Segmentation cites this paper.
Quality-Guided Semi-Supervised Learning for Medical Image Segmentation Leveraging Uncertainty Estimates for Predicting Segmentation Quality
Reference 10
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-01T22:06:16.683259Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.