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Paper Citation Record · LEDGER

A multi-centre polyp detection and segmentation dataset for generalisability assessment

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2106.04463.

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

pith.paper-citation-record.v1
2106.04463 v3

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 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:13:24.147629Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T14:00:13.094905Z

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 05922bbe-4a58-4cc9-b328-4fb0f64d07e4 · inbound

Enabling Real-Time Colonoscopic Polyp Segmentation on Commodity CPUs via Ultra-Lightweight Architecture cites this paper.

Enabling Real-Time Colonoscopic Polyp Segmentation on Commodity CPUs via Ultra-Lightweight Architecture A multi-centre polyp detection and segmentation dataset for generalisability assessment

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-21T14:00:13.097282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-21T13:57:41.526340Z digest=sha256:0cacbaa61dc27232fad29ebdbe500580cd2b9d22da9dee141cc89459d1fbb0f4

Observation ec181c0d-cf33-4b39-8dee-6ece2074c23b · inbound

PolypVision: A Three-Stage Hierarchical Deep Learning Framework for Classification and Segmentation of Colorectal Polyps cites this paper.

PolypVision: A Three-Stage Hierarchical Deep Learning Framework for Classification and Segmentation of Colorectal Polyps A multi-centre polyp detection and segmentation dataset for generalisability assessment

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-12T20:13:24.147629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:13:24.147629Z digest=sha256:93efcea876a5a2c931237e7ed6ded7b2f0209301a7bd8547bdb8186734becb5a