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Paper Citation Record · LEDGER

Hierarchical Bayesian inference of galaxy redshift distributions from photometric surveys

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1602.05960.

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

pith.paper-citation-record.v1
1602.05960 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T11:50:26.030339Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-06-30T01:04:08.847895Z

Reference resolution

0 of 0 outbound references displayed

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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 5006a1f5-34b7-40fd-91a0-ac08c0f69b88 · inbound

Machine Learning Techniques for Astrophysics and Cosmology: Photometric Redshifts cites this paper.

Machine Learning Techniques for Astrophysics and Cosmology: Photometric Redshifts Hierarchical Bayesian inference of galaxy redshift distributions from photometric surveys

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:10:53.907623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-11T00:51:26.783868Z digest=sha256:cb5fa1b062d8471f6713b8482cb2dfda2ee124f7cbae7c27ea4536294447dd35

Observation aa27b30f-edc8-452e-97ed-8ebc896046d3 · inbound

KiDS+VIKING-450 cosmology with Bayesian hierarchical model redshift distributions cites this paper.

KiDS+VIKING-450 cosmology with Bayesian hierarchical model redshift distributions Hierarchical Bayesian inference of galaxy redshift distributions from photometric surveys

Reference 84

Resolution
verified exact
local_arxiv, observed 2026-05-15T03:24:55.010126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-07-11T11:50:26.030339Z digest=sha256:e427c5b07631c32646475472556eb54cf6dc24fb14ea159da85a947c4f1655cd

Observation 8184abb7-76fe-4326-a459-826a65758719 · inbound

pop-cosmos: Disentangling galaxy properties from observables using data-driven approaches cites this paper.

pop-cosmos: Disentangling galaxy properties from observables using data-driven approaches Hierarchical Bayesian inference of galaxy redshift distributions from photometric surveys

Reference 219

Resolution
verified exact
local_arxiv, observed 2026-06-27T13:50:57.279513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-07-11T11:50:26.030339Z digest=sha256:293d279e07a3283ac27feb29aea6d34df79ef16f4294be33b4facbd971a44f94

Observation 7c6291fd-8140-4dcb-b6b9-f66dd509550a · inbound

pop-cosmos: Galaxy size evolution across structural and star-formation classifications in COSMOS-Web cites this paper.

pop-cosmos: Galaxy size evolution across structural and star-formation classifications in COSMOS-Web Hierarchical Bayesian inference of galaxy redshift distributions from photometric surveys

Reference 221

Resolution
verified exact
local_arxiv, observed 2026-06-30T01:04:08.849561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-07-11T11:50:26.030339Z digest=sha256:104dbd5155f52c2872ed0e77966b6af8b24666a434d08fd95581d957949b0f0d