Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Data-efficient multi-fidelity training for high-fidelity machine learning interatomic potentials
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2409.07947.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-16T23:16:47.814591Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T23:18:39.775834Z
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 5f759db2-92d0-47bd-a54f-1cd649633130 · inbound
AI-Driven Expansion and Application of the Alexandria Database cites this paper.
AI-Driven Expansion and Application of the Alexandria Database Data-efficient multi-fidelity training for high-fidelity machine learning interatomic potentials
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T23:18:39.777699Z
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.