Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Applying generative neural networks for fast simulations of the ALICE (CERN) experiment
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2407.16704.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T14:43:01.940606Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T14:43:02.001638Z
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 01a581ed-1dbe-4e80-99d2-0d7fddf7e451 · inbound
ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts cites this paper.
ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Applying generative neural networks for fast simulations of the ALICE (CERN) experiment
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T14:43:02.005571Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.