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Paper Citation Record · LEDGER

A volumetric deep Convolutional Neural Network for simulation of mock dark matter halo catalogues

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1805.04537.

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

pith.paper-citation-record.v1
1805.04537 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:29:19.373206Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-19T01:46:58.025850Z

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 5479e649-f1d1-4c44-ba2a-677bc93c51f5 · inbound

Differentiable Halo Mass Prediction and the Cosmology-Dependence of Halo Mass Functions cites this paper.

Differentiable Halo Mass Prediction and the Cosmology-Dependence of Halo Mass Functions A volumetric deep Convolutional Neural Network for simulation of mock dark matter halo catalogues

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T20:29:19.373206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:29:19.373206Z digest=sha256:0533ab016b3eaa441f998aa8ff375bf015985141adec0c32d9e57c64fc3da6c8

Observation 091f5df2-279f-4b30-8f5e-c00fd374fdfc · inbound

Segmenting proto-halos with vision transformers cites this paper.

Segmenting proto-halos with vision transformers A volumetric deep Convolutional Neural Network for simulation of mock dark matter halo catalogues

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-05-19T01:46:58.028734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-19T01:43:50.077818Z digest=sha256:bd2aa856a0043c33d001b78a0dbca88e6806ea24779458e2c082a3f9415b3ecd

Observation 2ce4d9ad-fa97-430a-b531-7041d677d17b · inbound

Emulating Cosmic Structure Formation with a Lagrangian Neural Cellular Automaton cites this paper.

Emulating Cosmic Structure Formation with a Lagrangian Neural Cellular Automaton A volumetric deep Convolutional Neural Network for simulation of mock dark matter halo catalogues

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-01T09:37:46.790594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T09:37:46.790594Z digest=sha256:601976376d76376c388934ee3a815ab05499eff8b23df9468e999b24af3210d6