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Paper Citation Record · LEDGER

Photometry and Photometric Redshift catalogs for the Lockman Hole Deep Field

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1110.0960.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1110.0960 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T21:02:25.785051Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

52
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 548b5e5e-66a9-4d37-9fe9-fb4e9bf064b7 · inbound

The Lockman-SpReSO Project: A Deep X-ray Spectral View of a FIR-selected AGN Population cites this paper.

The Lockman-SpReSO Project: A Deep X-ray Spectral View of a FIR-selected AGN Population Photometry and Photometric Redshift catalogs for the Lockman Hole Deep Field

Reference 85

Resolution
verified exact
local_arxiv, observed 2026-06-30T01:54:11.363546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-11T11:50:26.030339Z digest=sha256:67b2ef73ad7e7725fcc81fdad2a28517c78d73d21a8d5ad987b03d6614957dbf

Observation fc48b211-d2e5-4a7a-9406-178c57c2a8b9 · inbound

VAR-PZnn: A machine-learning framework for AGN photometric redshifts using color and variability-based features cites this paper.

VAR-PZnn: A machine-learning framework for AGN photometric redshifts using color and variability-based features Photometry and Photometric Redshift catalogs for the Lockman Hole Deep Field

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-01T21:02:25.785051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:02:25.785051Z digest=sha256:c98762c5177aa095a4bd9fc9c43f124bf8da6363125757cd35ee749110f0dded