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Paper Citation Record · LEDGER

Accelerating point defect photo-emission calculations with machine learning interatomic potentials

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2505.01403.

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

pith.paper-citation-record.v1
2505.01403 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 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T22:41:46.289356Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T22:41:52.891880Z

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 7937193d-63b1-4356-a72b-3c9489df2a0d · inbound

Machine Learning Phonon Spectra for Fast and Accurate Optical Lineshapes of Defects cites this paper.

Machine Learning Phonon Spectra for Fast and Accurate Optical Lineshapes of Defects Accelerating point defect photo-emission calculations with machine learning interatomic potentials

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:41:52.895996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T22:41:46.289356Z digest=sha256:80dfd51f5cf7877e93a1bd2bf17c8c7517b57d39106fa39a72e03762a19ff73b

Observation 94f4ee8a-f909-4b01-bffe-f384591767a4 · inbound

AI-Driven Expansion and Application of the Alexandria Database cites this paper.

AI-Driven Expansion and Application of the Alexandria Database Accelerating point defect photo-emission calculations with machine learning interatomic potentials

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-16T23:18:39.764410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-16T23:16:47.814591Z digest=sha256:220ceb418a98b6552ed9a2d12260d63134378f96c927deed84481de3876bfa58