Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Detection and Classification of Supernova Gravitational Waves Signals: A Deep Learning Approach
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1912.13517.
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 2026-08-16T00:45:53.070506Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T03:33:56.129018Z
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 6b0a9e42-5778-4e07-b586-e2bd475ffd17 · 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 Detection and Classification of Supernova Gravitational Waves Signals: A Deep Learning Approach
Reference 109
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:42:49.960753Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e825a64-aa1d-43ba-b608-a1408621bd07 · inbound
Can Transformers help us perform parameter estimation of overlapping signals in gravitational wave detectors? cites this paper.
Can Transformers help us perform parameter estimation of overlapping signals in gravitational wave detectors? Detection and Classification of Supernova Gravitational Waves Signals: A Deep Learning Approach
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:45:53.070506Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 542742f9-07cc-409e-ae2d-aa706dbc7eed · inbound
Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection cites this paper.
Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection Detection and Classification of Supernova Gravitational Waves Signals: A Deep Learning Approach
Reference 101
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T03:33:56.130633Z
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.