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Paper Citation Record · LEDGER

Explaining dark matter halo density profiles with neural networks

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.03077.

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

pith.paper-citation-record.v1
2305.03077 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:33:58.252309Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T20:44:21.878741Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • 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 16c319f5-3b92-444d-ad38-71ea09d6c1f2 · inbound

$\Lambda$CDM and early dark energy in latent space: a data-driven parametrization of the CMB temperature power spectrum cites this paper.

$\Lambda$CDM and early dark energy in latent space: a data-driven parametrization of the CMB temperature power spectrum Explaining dark matter halo density profiles with neural networks

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T20:33:58.252309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:33:58.252309Z digest=sha256:0ddb5d7e41037b34bf4ecc2506e4386daedf30d284ca0f9ea92577cd48cc2833

Observation 05101322-3d01-48be-a762-caca418140c5 · inbound

QUEST (Quasar Unsupervised Encoder and Synthesis Tool): A machine learning framework to generate quasar spectra cites this paper.

QUEST (Quasar Unsupervised Encoder and Synthesis Tool): A machine learning framework to generate quasar spectra Explaining dark matter halo density profiles with neural networks

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-21T20:44:21.881753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-21T20:44:03.869989Z digest=sha256:28c16e282b17a8df6eb06888e3a8021c189bbf5ebd7c43a6778fcdbdf8db28ab