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Paper Citation Record · LEDGER

A practical guide to machine learning interatomic potentials -- Status and future

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.09814.

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

pith.paper-citation-record.v1
2503.09814 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-09T10:41:42.067218Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T10:46:11.666598Z

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 4f686f5d-b257-48d8-b88a-efd5d759ecf4 · inbound

Distilling first-principles accuracy into compact machine learning potentials for condensed-phase chemistry cites this paper.

Distilling first-principles accuracy into compact machine learning potentials for condensed-phase chemistry A practical guide to machine learning interatomic potentials -- Status and future

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-02T20:07:22.565853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T20:50:41.513859Z digest=sha256:e5112d650b493a6257d3bf846a7a3a3af18beb4169c4446cffd2f3a33697a00e

Observation 4b8cca31-2271-4736-9452-982170be278a · inbound

A Multi-Scale Machine Learning Framework for Coupled Chemical, Spin, and Structural Disorder in Alloys cites this paper.

A Multi-Scale Machine Learning Framework for Coupled Chemical, Spin, and Structural Disorder in Alloys A practical guide to machine learning interatomic potentials -- Status and future

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-07-09T10:46:11.667882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-09T10:41:42.067218Z digest=sha256:582d0564bf1d78999dd8a463d400ab4a2b897b36ee7c100cb6b0f006fd92925e