Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks
As of 15 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1709.04205.
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 2026-07-15T06:30:58.975436+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-11T11:50:26.030339Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-09T08:05:16.230513Z
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 9d769565-9583-48ee-90cd-de606f203bae · inbound
From DES to KiDS: Domain adaptation for cross-survey detection of low-surface-brightness galaxies cites this paper.
From DES to KiDS: Domain adaptation for cross-survey detection of low-surface-brightness galaxies Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-14T17:47:31.890289Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.
Observation c19f268d-bd75-4c6c-857f-541ddb7f55d6 · inbound
KiDS+VIKING-450 cosmology with Bayesian hierarchical model redshift distributions cites this paper.
KiDS+VIKING-450 cosmology with Bayesian hierarchical model redshift distributions Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks
Reference 59
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T03:24:54.966603Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.