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Paper Citation Record · LEDGER

Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2306.06929.

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

pith.paper-citation-record.v1
2306.06929 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:42:49.940719Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:39:05.241730Z

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 dd21c15f-a3ce-4602-ac36-39b077f8b9d3 · 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 Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks

Reference 105

Resolution
unresolved
no resolver link, observed 2026-08-11T11:42:49.940719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 95d01186-0576-4fe3-a880-e76e97d15870 · inbound

Physics-Driven Learning for Inverse Problems in Quantum Chromodynamics cites this paper.

Physics-Driven Learning for Inverse Problems in Quantum Chromodynamics Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-10T21:15:54.631628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1f6e8374-2b6c-40f4-af40-0cea59fb2fdb · inbound

Exploring the limits of nucleonic metamodelling using different relativistic density functionals cites this paper.

Exploring the limits of nucleonic metamodelling using different relativistic density functionals Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-08T23:14:27.556366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ab01acdb-6bb7-412d-a74a-968c2df209b1 · inbound

Locating the QCD critical point with neutron-star observations cites this paper.

Locating the QCD critical point with neutron-star observations Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T04:40:52.717633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:40:52.717633Z digest=sha256:a038e2809d795a133d2f8301d287dcfe3d092554fcd5231136d6c2de23b186ec

Observation eb1a78eb-de99-4843-83e2-eee47bdffc9d · inbound

Topological Uncertainty for Anomaly Detection in the Neural-network EoS Inference with Neutron Star Data cites this paper.

Topological Uncertainty for Anomaly Detection in the Neural-network EoS Inference with Neutron Star Data Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:39:05.245013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T15:39:05.014178Z digest=sha256:ce5cc35d6d020c173a3c44fd69a52b08899adee4fbd74e66715e76fd9394ff96

Observation ce99c5dc-4b73-43f0-ac5a-e83b484a888d · inbound

Fast and Accurate Prediction of Neutron Star Structure with Deep Neural Networks cites this paper.

Fast and Accurate Prediction of Neutron Star Structure with Deep Neural Networks Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-11T00:26:46.638146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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