Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1810.08217.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:05:07.287052Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T16:46:20.156732Z
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 3fa2b1bb-94b1-423b-8052-3571b98da272 · inbound
AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks cites this paper.
AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:05:07.287052Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 72c1cbd0-91ee-4ca4-94a6-3289b15f0013 · inbound
Loop2Net: Data-Driven Generation and Optimization of Airfoil CFD Meshes from Sparse Boundary Coordinates cites this paper.
Loop2Net: Data-Driven Generation and Optimization of Airfoil CFD Meshes from Sparse Boundary Coordinates Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:59:15.533768Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 642436c7-4d53-45c7-9ffc-9dd6bdd65473 · inbound
Mesh Based Simulations with Spatial and Temporal awareness cites this paper.
Mesh Based Simulations with Spatial and Temporal awareness Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T16:46:20.295132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.