Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Identifying eclipsing binary stars with TESS data based on a new hybrid deep learning model
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2504.15875.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:20:41.174298Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T19:22:25.409856Z
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 a9d517ac-4dd1-4470-a8d7-cbbc60c5cb70 · inbound
The TESS Ten Thousand Catalog: 10,001 uniformly-vetted and -validated Eclipsing Binary Stars detected in Full-Frame Image data by machine learning and analyzed by citizen scientists cites this paper.
The TESS Ten Thousand Catalog: 10,001 uniformly-vetted and -validated Eclipsing Binary Stars detected in Full-Frame Image data by machine learning and analyzed by citizen scientists Identifying eclipsing binary stars with TESS data based on a new hybrid deep learning model
Reference 115
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:20:41.174298Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 30b6be9d-3306-4711-a1f3-49a677e910f5 · inbound
Morphological classification of eclipsing binary stars using computer vision methods cites this paper.
Morphological classification of eclipsing binary stars using computer vision methods Identifying eclipsing binary stars with TESS data based on a new hybrid deep learning model
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T19:22:25.506451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.