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Paper Citation Record · LEDGER

Applying the Viterbi Algorithm to Planetary-Mass Black Hole Searches

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2401.02314.

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

pith.paper-citation-record.v1
2401.02314 v3

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 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:42:49.637955Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T17:18:47.332502Z

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 9f0b7239-62ec-46b7-af0d-216294360d8f · inbound

Applications of machine learning in gravitational wave research with current interferometric detectors cites this paper.

Applications of machine learning in gravitational wave research with current interferometric detectors Applying the Viterbi Algorithm to Planetary-Mass Black Hole Searches

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T11:42:49.637955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:42:49.637955Z digest=sha256:da94fa95d12d69217e9c91d1ef8f4b41899b8b9f43601fe4143ed7e6bda6533c

Observation e8cbb77e-a8bf-4400-a361-634a8cec2318 · inbound

BinaryGFH-v2: Improved method to search for gravitational waves from sub-solar-mass, ultra-compact binaries using the Generalized Frequency-Hough Transform cites this paper.

BinaryGFH-v2: Improved method to search for gravitational waves from sub-solar-mass, ultra-compact binaries using the Generalized Frequency-Hough Transform Applying the Viterbi Algorithm to Planetary-Mass Black Hole Searches

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-03T17:13:00.638856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:13:00.638856Z digest=sha256:a7d42ab4dc306801953bcce7654296c55a1433358dc9a0e664fe7e501e3bee67

Observation 8c21a0c8-dcd9-4e65-a3af-7b37c031d346 · inbound

Constraints on primordial black holes from the first part of LIGO-Virgo-KAGRA fourth observing run cites this paper.

Constraints on primordial black holes from the first part of LIGO-Virgo-KAGRA fourth observing run Applying the Viterbi Algorithm to Planetary-Mass Black Hole Searches

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-20T17:18:47.335186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-20T17:15:51.364347Z digest=sha256:4a2a989e4f4f24cf0b603daa16b24a3f697a3be127c3a7268dde9d11047d1f1e

Observation 6b10c6f1-bdcf-4f9e-9347-80f30fbe6d49 · inbound

Constraints on primordial black holes from the first part of LIGO-Virgo-KAGRA fourth observing run cites this paper.

Constraints on primordial black holes from the first part of LIGO-Virgo-KAGRA fourth observing run Applying the Viterbi Algorithm to Planetary-Mass Black Hole Searches

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-02T13:59:29.853931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:59:29.853931Z digest=sha256:e5c6a7d83f9e4170d0e90a164f4e4db61eb501be636ce49304425a9e8f3ea787