Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Accelerating cosmological inference with Gaussian processes and neural networks -- an application to LSST Y1 weak lensing and galaxy clustering
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2203.06124.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:31:03.597104Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T06:15:58.374505Z
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 d56a968e-b984-4d64-a0be-fbd6c9c4f05e · inbound
Emulating Recombination with Neural Networks using Universal Differential Equations cites this paper.
Emulating Recombination with Neural Networks using Universal Differential Equations Accelerating cosmological inference with Gaussian processes and neural networks -- an application to LSST Y1 weak lensing and galaxy clustering
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:31:03.597104Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c613575d-8bab-47cc-b1e5-c33c99921fe8 · inbound
Modeling nonlinear scales for dynamical dark energy cosmologies with COLA cites this paper.
Modeling nonlinear scales for dynamical dark energy cosmologies with COLA Accelerating cosmological inference with Gaussian processes and neural networks -- an application to LSST Y1 weak lensing and galaxy clustering
Reference 134
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T06:15:58.376858Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.