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Paper Citation Record · LEDGER

Robustness of deep learning algorithms in astronomy -- galaxy morphology studies

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2111.00961.

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

pith.paper-citation-record.v1
2111.00961 v2

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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:11:38.671035Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:11:37.647049Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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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 2fe2ee8d-9b9f-4758-91c7-3eff98b5b798 · inbound

Galaxy Morphological Classification with Manifold Learning cites this paper.

Galaxy Morphological Classification with Manifold Learning Robustness of deep learning algorithms in astronomy -- galaxy morphology studies

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-11T17:11:38.671035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:11:38.671035Z digest=sha256:ecee9a9ada6aa81e0520ed00b1a4ad1e3ec038f9b295643256ca4860fc456514

Observation f6f64344-7cdc-44c4-bed1-d7c723637346 · inbound

Enhancing Galaxy Classification with U-Net Variational Autoencoders for Image Denoising cites this paper.

Enhancing Galaxy Classification with U-Net Variational Autoencoders for Image Denoising Robustness of deep learning algorithms in astronomy -- galaxy morphology studies

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:11:37.709502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-06T23:11:34.536328Z digest=sha256:6c4a6890b38392e037562c53d15bebd277410429cb1c649ca8b287a92b2b29c7