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Paper Citation Record · LEDGER

A machine learning approach to the classification of phase transitions in many flavor QCD

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.16232.

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

pith.paper-citation-record.v1
2211.16232 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:42:07.942793Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T04:10:58.401533Z

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 86346a47-da52-4356-98be-e0895e654313 · inbound

Lattice gauge ensembles and data management cites this paper.

Lattice gauge ensembles and data management A machine learning approach to the classification of phase transitions in many flavor QCD

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-08T05:42:07.942793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:42:07.942793Z digest=sha256:805179dd9af44a05b343db75157d0360bb1128fdfc65e2da56a89d30aedb0e9c

Observation 07e469f1-f94c-40f9-9d61-d7dbeeae9426 · inbound

Testing machine-learned distributions against Monte Carlo data for the QCD chiral phase transition cites this paper.

Testing machine-learned distributions against Monte Carlo data for the QCD chiral phase transition A machine learning approach to the classification of phase transitions in many flavor QCD

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:10:58.407078Z

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=2026-05-11T01:54:10.924145Z digest=sha256:0e882618a0329fab9a8cb11efa9ace019cb38f76ade1bf06dcb5c277419a89b2