Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Inferring viscoplastic models from velocity fields: a physics-informed neural network approach
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2506.17681.
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 2026-06-29T05:08:29.300278Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T18:23:51.184122Z
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 1faa4148-8455-4f71-a770-2cedea02696e · inbound
Neural-Network-based Viscosity Closure for Non-Newtonian Multiphase Flows cites this paper.
Neural-Network-based Viscosity Closure for Non-Newtonian Multiphase Flows Inferring viscoplastic models from velocity fields: a physics-informed neural network approach
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T18:23:51.185618Z
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.