Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T13:06:38.879870Z
Paper Citation Record · LEDGER
Symmetry- and Gradient-enhanced Gaussian Process Regression for the Active Learning of Potential Energy Surfaces in Porous Materials
As of 11 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 0 inbound Pith citation observations for arXiv:2501.16475.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
3 of 3 outbound references displayed
- verified exact1
- verified fuzzy0
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation be57693d-71e7-4273-af6d-754154160282 · outbound
This paper cites an unresolved cited work.
Symmetry- and Gradient-enhanced Gaussian Process Regression for the Active Learning of Potential Energy Surfaces in Porous Materials Unresolved cited work
Reference 1
- Resolution
- verified exact
- doi, observed 2026-08-10T13:06:38.960666Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation d0a96009-9fb2-4afc-9121-5c72c962ea8d · outbound
This paper cites $\texttt{Spglib}$: a software library for crystal symmetry search.
Symmetry- and Gradient-enhanced Gaussian Process Regression for the Active Learning of Potential Energy Surfaces in Porous Materials $\texttt{Spglib}$: a software library for crystal symmetry search
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T13:06:38.879870Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a3bdd94d-9c91-408d-9122-dccf1ca02304 · outbound
This paper cites an unresolved cited work.
Symmetry- and Gradient-enhanced Gaussian Process Regression for the Active Learning of Potential Energy Surfaces in Porous Materials Unresolved cited work
Reference 30
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T13:06:38.941753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Pith citing papers
No inbound Pith citation observations are available.