Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Weak lensing shear estimation beyond the shape-noise limit: a machine learning approach
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1808.07491.
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 2026-08-14T10:47:27.931438Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-12T18:48:42.687710Z
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 c1d2ce3e-6024-4577-9592-afb09f9e0247 · inbound
Cosmological parameter estimation from large-scale structure deep learning cites this paper.
Cosmological parameter estimation from large-scale structure deep learning Weak lensing shear estimation beyond the shape-noise limit: a machine learning approach
Reference 76
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T10:47:27.931438Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 018d2ad5-ea06-4450-881d-9b13674ea85f · inbound
AI-Powered Reconstruction of Dark Matter Velocity Fields from Redshift-Space Halo Distribution cites this paper.
AI-Powered Reconstruction of Dark Matter Velocity Fields from Redshift-Space Halo Distribution Weak lensing shear estimation beyond the shape-noise limit: a machine learning approach
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T18:48:42.693955Z
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.