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Paper Citation Record · LEDGER

Using Deep Learning to Identify Artificial Satellite Trails in Multi-band Photometric Astronomical Images

As of 8 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 0 inbound Pith citation observations for arXiv:2509.04081.

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

pith.paper-citation-record.v1
2509.04081 v1

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:29:11.845199Z

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

2 of 2 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d4ba9722-216b-472b-9c1b-0300eea5ba48 · outbound

This paper cites Rubin ToO 2024: Envisioning the Vera C. Rubin Observatory LSST Target of Opportunity program.

Using Deep Learning to Identify Artificial Satellite Trails in Multi-band Photometric Astronomical Images Rubin ToO 2024: Envisioning the Vera C. Rubin Observatory LSST Target of Opportunity program

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T10:29:11.841227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:29:11.841227Z digest=sha256:717063227088165972017c6a3dc400baaa2639e2f892144081602db68394887c

Observation 0013666b-0d36-434d-ac9f-dc754024a85e · outbound

This paper cites Squeeze-and-Excitation Networks.

Using Deep Learning to Identify Artificial Satellite Trails in Multi-band Photometric Astronomical Images Squeeze-and-Excitation Networks

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T10:29:11.845199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:29:11.845199Z digest=sha256:c6fdd7f9fd143df7ce2af87c122dd862b31a946e21db8e6011be7c7303c84e6f

Pith citing papers

No inbound Pith citation observations are available.