Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Active flow control for drag reduction through multi-agent reinforcement learning on a turbulent cylinder at $Re_D=3900$
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.17655.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T11:30:39.713398Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T09:35:40.861780Z
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 e009da40-0acf-419c-a966-582104f7fbf7 · inbound
Separation control applied to the turbulent flow around a NACA4412 wing section cites this paper.
Separation control applied to the turbulent flow around a NACA4412 wing section Active flow control for drag reduction through multi-agent reinforcement learning on a turbulent cylinder at $Re_D=3900$
Reference 1261
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T11:30:39.713398Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 184ba6ff-7412-4f9d-9b95-dd77bf0cd994 · inbound
Offline Reinforcement Learning for Fluid Controls: Data-based Multi-observational Policy Extraction cites this paper.
Offline Reinforcement Learning for Fluid Controls: Data-based Multi-observational Policy Extraction Active flow control for drag reduction through multi-agent reinforcement learning on a turbulent cylinder at $Re_D=3900$
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T09:35:40.863614Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.