Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Towards a robust and reliable deep learning approach for detection of compact binary mergers in gravitational wave data
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.11797.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T11:42:50.502183Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T05:30:32.263650Z
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 58d39fc1-5c06-4d78-b791-012325345741 · inbound
Applications of machine learning in gravitational wave research with current interferometric detectors cites this paper.
Applications of machine learning in gravitational wave research with current interferometric detectors Towards a robust and reliable deep learning approach for detection of compact binary mergers in gravitational wave data
Reference 217
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:42:50.502183Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b15487af-2dd2-425f-adba-927ab77cf664 · inbound
Robustness of Sensitivity Evaluations for Gravitational Wave Detection Algorithms cites this paper.
Robustness of Sensitivity Evaluations for Gravitational Wave Detection Algorithms Towards a robust and reliable deep learning approach for detection of compact binary mergers in gravitational wave data
Reference 65
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T05:30:32.271413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.