Paper Citation Record · LEDGER

Machine Learning Assisted NEO Discovery and Polarimetric Characterisation with Astronomical Surveys

As of 6 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 0 inbound Pith citation observations for arXiv:2604.02999.

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

pith.paper-citation-record.v1
2604.02999 v1

Coverage vector

measured 4 of 4 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-13T18:24:15.329348Z

measured 4 of 4 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

4 of 4 outbound references displayed

verified exact1
verified fuzzy3
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1868c8d6-bed0-4f1e-840d-c5d0778d182f · outbound

This paper cites Verdoes Kleijn (1) , T.

Machine Learning Assisted NEO Discovery and Polarimetric Characterisation with Astronomical Surveys Verdoes Kleijn (1) , T

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T04:16:36.316406Z

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.

Observation c0826478-3885-44f9-87db-5af723b73304 · outbound

This paper cites Our group also includes members of the Rubin Consortium who are interested in taking the lessons learned from Euclid and OmegaCAM to the LSST survey.

Machine Learning Assisted NEO Discovery and Polarimetric Characterisation with Astronomical Surveys Our group also includes members of the Rubin Consortium who are interested in taking the lessons learned from Euclid and OmegaCAM to the LSST survey

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T04:16:36.312177Z

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.

Observation c15d274d-5ab3-48d8-843f-eece1ca4f508 · outbound

This paper cites test particles.

Machine Learning Assisted NEO Discovery and Polarimetric Characterisation with Astronomical Surveys test particles

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T04:16:36.320503Z

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.

Observation d75237da-519b-4118-a2cd-52c2dbaeaa2b · outbound

This paper cites Mellier, Abdurro’uf, J.

Machine Learning Assisted NEO Discovery and Polarimetric Characterisation with Astronomical Surveys Mellier, Abdurro’uf, J

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:28:06.601166Z

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.

Pith citing papers

No inbound Pith citation observations are available.