Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Flow control by a hybrid use of machine learning and control theory
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2311.08624.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T16:37:37.267799Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T16:37:37.624885Z
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 23dfe247-7310-4664-bddd-328f68af3434 · inbound
Latent feedback control of distributed systems in multiple scenarios through deep learning-based reduced order models cites this paper.
Latent feedback control of distributed systems in multiple scenarios through deep learning-based reduced order models Flow control by a hybrid use of machine learning and control theory
Reference 37
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T16:37:37.629864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.