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Paper Citation Record · LEDGER

Toward Filament Segmentation Using Deep Neural Networks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1912.02743.

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

pith.paper-citation-record.v1
1912.02743 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:33:49.985190Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T15:03:31.920273Z

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 70d99a4d-cb45-4db8-98b6-c271af35b011 · inbound

Large Model Driven Solar Activity AI Forecaster: A Scalable Dual Data-Model Framework cites this paper.

Large Model Driven Solar Activity AI Forecaster: A Scalable Dual Data-Model Framework Toward Filament Segmentation Using Deep Neural Networks

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T22:33:49.985190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:33:49.985190Z digest=sha256:9cec48e42fd12d42688cd0651d12c6b9ea13930cf090cb81ccd42c1369ec120d

Observation ed1dc3d7-c16a-4e9e-9c4e-ce816e46f935 · inbound

Automated void identification by Blendmask: from hierarchical molecular gas to hierarchical voids in NGC 628 cites this paper.

Automated void identification by Blendmask: from hierarchical molecular gas to hierarchical voids in NGC 628 Toward Filament Segmentation Using Deep Neural Networks

Reference 2

Resolution
malformed identifier
arxiv_id, observed 2026-06-29T15:03:31.922042Z

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.

source=pdf_text observed=2026-06-29T06:05:22.636697Z digest=sha256:a6ddc8f7c544f41b4d29518ef3b7e6f9d25e5c8c465f8e65769ae5aace13e909