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Paper Citation Record · LEDGER

Cosmological Inference using Gravitational Waves and Normalising Flows

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2310.13405.

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

pith.paper-citation-record.v1
2310.13405 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:29:10.181153Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T09:06:26.354850Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • parse uncertain0
  • malformed identifier0
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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 1ddbf105-1bde-4921-b53d-a50ff42bfc4f · inbound

Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State cites this paper.

Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State Cosmological Inference using Gravitational Waves and Normalising Flows

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-11T22:29:10.181153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:29:10.181153Z digest=sha256:cd0b7e768b8621d292054ae43e9dca871f70ec35e80caa0eb5af136f60314cdb

Observation 62aa119e-1775-43eb-8244-296cfbf3d9cf · inbound

Learning from galactic rotation curves: a neural network approach cites this paper.

Learning from galactic rotation curves: a neural network approach Cosmological Inference using Gravitational Waves and Normalising Flows

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-11T22:21:35.422610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:21:35.422610Z digest=sha256:ae04b89d7cd414e10fa98122f7b28239fa3ad20ed462b1e3676dda3e301f01b3

Observation de731f53-73b4-44d8-8f6a-9d1ec17843bb · inbound

Normalizing flows for density estimation in multi-detector gravitational-wave searches cites this paper.

Normalizing flows for density estimation in multi-detector gravitational-wave searches Cosmological Inference using Gravitational Waves and Normalising Flows

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:06:26.357571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-07T12:53:40.252894Z digest=sha256:f5b7871dfa78addbec223ab9ec0b0f3dd3a07cdb448667467e5e5a533efa42a3