Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:40:56.082297Z
Paper Citation Record · LEDGER
A novel hybrid neural network of fluid-structure interaction prediction for two cylinders in tandem arrangement
As of 18 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 0 inbound Pith citation observations for arXiv:2504.14971.
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 2026-08-17T06:30:58.91139+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
6 of 6 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved6
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 9aace69d-8e60-468c-aca0-6f90de378e20 · outbound
This paper cites Fourier Neural Operator for Plasma Modelling.
A novel hybrid neural network of fluid-structure interaction prediction for two cylinders in tandem arrangement Fourier Neural Operator for Plasma Modelling
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:40:56.057951Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc713eb5-c22e-44a4-b3e4-f387d32be9dd · outbound
This paper cites an unresolved cited work.
A novel hybrid neural network of fluid-structure interaction prediction for two cylinders in tandem arrangement Unresolved cited work
Reference 28
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:40:56.140123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ee1479f9-d7ed-4079-a3d1-00ac70794086 · outbound
This paper cites Compressed Convolutional LSTM: An Efficient Deep Learning framework to Model High Fidelity 3D Turbulence.
A novel hybrid neural network of fluid-structure interaction prediction for two cylinders in tandem arrangement Compressed Convolutional LSTM: An Efficient Deep Learning framework to Model High Fidelity 3D Turbulence
Reference 827
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:40:56.071071Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae2db785-7b97-4d1d-91cf-545b7621b289 · outbound
This paper cites an unresolved cited work.
A novel hybrid neural network of fluid-structure interaction prediction for two cylinders in tandem arrangement Unresolved cited work
Reference 893
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:40:56.150001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0deab3a0-9713-43cc-afcd-e4d36aee9f7c · outbound
This paper cites an unresolved cited work.
A novel hybrid neural network of fluid-structure interaction prediction for two cylinders in tandem arrangement Unresolved cited work
Reference 1566
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:40:56.159680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5bd19ec3-141b-4ec5-8da9-b1884c4ca16b · outbound
This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.
A novel hybrid neural network of fluid-structure interaction prediction for two cylinders in tandem arrangement Fourier Neural Operator for Parametric Partial Differential Equations
Reference 1780
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:40:56.066391Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.