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Paper Citation Record · LEDGER

A representation learning approach to probe for dynamical dark energy in matter power spectra

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.10717.

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

pith.paper-citation-record.v1
2310.10717 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:33:58.099163Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T04:45:24.580638Z

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 a3192c34-1d20-490d-ac11-36eb4717a0d8 · inbound

Interpretability of deep-learning methods applied to large-scale structure surveys cites this paper.

Interpretability of deep-learning methods applied to large-scale structure surveys A representation learning approach to probe for dynamical dark energy in matter power spectra

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:45:24.583641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T04:43:25.035106Z digest=sha256:f2be79b77e47e967f40198f2f62ab4463658ebd903afdc7b227f1547adcad699

Observation 8f12619a-2337-4d65-92f7-595e5cab5084 · 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 A representation learning approach to probe for dynamical dark energy in matter power spectra

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T20:33:58.099163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:33:58.099163Z digest=sha256:92dce55baa589bac33dd987d5421de33e5bb9e06435cb8c6076983cfe1fd0cd2