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Paper Citation Record · LEDGER

Machine Learning in Physics and Geometry

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2303.12626.

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

pith.paper-citation-record.v1
2303.12626 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:49:48.901163Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:55:39.446683Z

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 a2d0976e-bd85-4d01-943d-828f77c00a2d · inbound

Advancing Geometry with AI: Multi-agent Generation of Polytopes cites this paper.

Advancing Geometry with AI: Multi-agent Generation of Polytopes Machine Learning in Physics and Geometry

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-09T22:49:48.901163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T22:49:48.901163Z digest=sha256:14bd588a616921d4ceeeecfde6d5bc69412cb61787205135e877309b28aa7132

Observation 599eea54-89f3-44bf-b293-8348adee1b6b · inbound

Enhancing Meme Token Market Transparency: A Multi-Dimensional Entity-Linked Address Analysis for Liquidity Risk Evaluation cites this paper.

Enhancing Meme Token Market Transparency: A Multi-Dimensional Entity-Linked Address Analysis for Liquidity Risk Evaluation Machine Learning in Physics and Geometry

Reference 26

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T14:55:39.493678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T14:55:38.253970Z digest=sha256:236eb208f0eeb2cbd37b7c301e39b3bb2b04716f25d08100dcb7a93cd9b6d659