Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategies
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.10720.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T15:51:42.481785Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T16:40:14.442570Z
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 7333975a-986d-42d6-a389-bff80f74d813 · inbound
Trajectory Tracking Using Frenet Coordinates with Deep Deterministic Policy Gradient cites this paper.
Trajectory Tracking Using Frenet Coordinates with Deep Deterministic Policy Gradient Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategies
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:51:42.481785Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2cf51b92-c9d5-43fb-ad82-0ba91fbc0bfd · inbound
Optimized Coordination Strategy for Multi-Aerospace Systems in Pick-and-Place Tasks By Deep Neural Network cites this paper.
Optimized Coordination Strategy for Multi-Aerospace Systems in Pick-and-Place Tasks By Deep Neural Network Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategies
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T16:40:14.450439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.