Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Global physics-informed neural networks (GPINNs): from local point-wise constraint to global nodal association
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2503.06403.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:13:21.744673Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T19:13:22.002547Z
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 b9c4caa0-89ce-4865-9501-0f57a38a36ff · inbound
Inferring viscoplastic models from velocity fields: a physics-informed neural network approach cites this paper.
Inferring viscoplastic models from velocity fields: a physics-informed neural network approach Global physics-informed neural networks (GPINNs): from local point-wise constraint to global nodal association
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T19:13:22.092972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.