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Paper Citation Record · LEDGER

Finding universal relations in subhalo properties with artificial intelligence

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2109.04484.

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

pith.paper-citation-record.v1
2109.04484 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:17:48.896081Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T09:21:20.740944Z

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 c1a68264-303f-4560-b7a5-d4270f00ce16 · inbound

SymbolFit: Automatic Parametric Modeling with Symbolic Regression cites this paper.

SymbolFit: Automatic Parametric Modeling with Symbolic Regression Finding universal relations in subhalo properties with artificial intelligence

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T20:17:48.896081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:17:48.896081Z digest=sha256:8e905d8d9cca50f16bf59f0cd71b7b008e88d5c01f8eea9f2544117c476a1468

Observation e7c19f2f-3ab3-409b-aba3-8fbf7e0fc125 · inbound

Predicting intermediate-mass black hole formation in star clusters with machine learning cites this paper.

Predicting intermediate-mass black hole formation in star clusters with machine learning Finding universal relations in subhalo properties with artificial intelligence

Reference 90

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:21:20.743081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-22T09:20:09.976842Z digest=sha256:ca5f5dd940cc5cc2b5e10ca9ca81ae85f9a1ad6647c8580264647bd15edb64da