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Paper Citation Record · LEDGER

Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2107.10210.

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

pith.paper-citation-record.v1
2107.10210 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 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T22:37:31.448084Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

60
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation fefdb68c-dda3-4886-b74f-cdc4cf297431 · inbound

Where Galaxies Point: First Measurement of the Large-Scale Axial Intrinsic Alignment cites this paper.

Where Galaxies Point: First Measurement of the Large-Scale Axial Intrinsic Alignment Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-03T22:37:31.448084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:37:31.448084Z digest=sha256:7f94751fa723c5ba5fcd5501719ac5d0ef8da1d924f9def3594b5edd2e3fbf20

Observation 67ab81f4-3d3a-4b7c-8d5b-2530a9fad058 · inbound

Uncertainty-Aware Deep Learning for the Ly$\alpha$ Forest: CNN-Based Absorber Detection and Characterization cites this paper.

Uncertainty-Aware Deep Learning for the Ly$\alpha$ Forest: CNN-Based Absorber Detection and Characterization Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-07-11T06:57:51.391677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-07-11T06:51:29.075290Z digest=sha256:d12a3da756add9b51d942646b5c305dd4ead9f56746eec18ffa95365f8593323