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Paper Citation Record · LEDGER

KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.07288.

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

pith.paper-citation-record.v1
2502.07288 v1

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 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T10:57:36.260257Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T13:53:28.489276Z

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 5d9992ae-e243-4a77-a588-e2fc33271686 · inbound

Controllable Diffusion-Based Lesion Inpainting for Scalable Histopathology Data Augmentation cites this paper.

Controllable Diffusion-Based Lesion Inpainting for Scalable Histopathology Data Augmentation KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-03T10:57:36.260257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:57:36.260257Z digest=sha256:3eaf87c0842046b3f095e15aff756757974d7ae8ad3a6385464a463e505f300f

Observation 0e4c5d53-bfa2-4402-bdbe-ee8fd4b2ff7b · inbound

MORI-Seg: Learning Morphological Geometry for Instance Segmentation without Instance Annotations cites this paper.

MORI-Seg: Learning Morphological Geometry for Instance Segmentation without Instance Annotations KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-29T13:53:28.491001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-29T13:52:32.362858Z digest=sha256:f3be6c59cbc3ec5e327165a1a4ee47154e5b0bb7c70ef28c9c2fe27e2308bc8a