Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1902.05950.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T14:41:19.740687Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T19:46:13.857778Z
Reference resolution
0 of 0 outbound references displayed
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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 bf3b9c2e-998d-44c8-9004-da1581abc3ec · inbound
Using X-Ray Morphological Parameters to Strengthen Galaxy Cluster Mass Estimates via Machine Learning cites this paper.
Using X-Ray Morphological Parameters to Strengthen Galaxy Cluster Mass Estimates via Machine Learning A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T14:41:19.740687Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b61ffa99-502a-4421-892a-3c5926911a28 · inbound
Comparative analysis of the NANOgrav Hellings-Downs as a window into new physics cites this paper.
Comparative analysis of the NANOgrav Hellings-Downs as a window into new physics A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters
Reference 74
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T13:35:31.333801Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6fe671e0-60d9-4c77-a755-27ece771524e · inbound
Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective cites this paper.
Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters
Reference 250
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T19:46:13.859446Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.