Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
NNETFIX: An artificial neural network-based denoising engine for gravitational-wave signals
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2101.04712.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:11:25.253305Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T12:45:24.116190Z
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 f2287b4d-6c5f-4bc9-85a0-23bf7190a3e0 · inbound
Black Hole Spectroscopy with Conditional Variational Autoencoder cites this paper.
Black Hole Spectroscopy with Conditional Variational Autoencoder NNETFIX: An artificial neural network-based denoising engine for gravitational-wave signals
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:11:25.253305Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 421c28a5-a554-4e92-8371-7efe41303cb3 · inbound
Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows cites this paper.
Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows NNETFIX: An artificial neural network-based denoising engine for gravitational-wave signals
Reference 95
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T12:45:24.117520Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.