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Paper Citation Record · LEDGER

Leveraging Uncertainty Estimates for Predicting Segmentation Quality

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1807.00502.

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

pith.paper-citation-record.v1
1807.00502 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:54:04.036914Z

measured 0 of 1 external citation measurements

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 3ec71ec6-8b7f-419f-99e6-83c11a92827e · inbound

EigenRank by Committee: A Data Subset Selection and Failure Prediction paradigm for Robust Deep Learning based Medical Image Segmentation cites this paper.

EigenRank by Committee: A Data Subset Selection and Failure Prediction paradigm for Robust Deep Learning based Medical Image Segmentation Leveraging Uncertainty Estimates for Predicting Segmentation Quality

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-14T12:54:04.036914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:54:04.036914Z digest=sha256:502b26e1fc995607e10f1e42135de4d0702450e7bbc4fcc55839ce7463215c32

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.

source=arxiv_source observed=2026-08-06T05:38:16.008468Z digest=sha256:0a6c895c5bedbc7123d986b8239eb5e281b372081e09c6fc58409a113c690374

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T15:44:32.345362Z digest=sha256:4c6468afe1b0671b059687aab12f95b09f44720b39b15bf5acfa7fe5a0c230d2