Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A thorough investigation of the prospects of eLISA in addressing the Hubble tension: Fisher Forecast, MCMC and Machine Learning
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2301.12708.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T15:22:44.333799Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T15:23:32.336466Z
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 1b732efc-a050-4d5f-9222-aec1273deb74 · inbound
Gaussian Process Reconstruction of Cosmological Parameters with Gravitational Wave Sirens using Machine Learning cites this paper.
Gaussian Process Reconstruction of Cosmological Parameters with Gravitational Wave Sirens using Machine Learning A thorough investigation of the prospects of eLISA in addressing the Hubble tension: Fisher Forecast, MCMC and Machine Learning
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T15:23:32.337918Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.