Paper Citation Record · LEDGER

Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2012.01317.

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

pith.paper-citation-record.v1
2012.01317 v3

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 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:42:34.800057Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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verified fuzzy0
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1f42b44f-c953-471f-9bbd-129a785b662d · inbound

Comparing astrophysical models to gravitational-wave data in the observable space cites this paper.

Comparing astrophysical models to gravitational-wave data in the observable space Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-19T04:37:03.807095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d670aef7-fb0b-40a5-9e0b-c09bf807fd22 · inbound

When (not) to trust Monte Carlo approximations for hierarchical Bayesian inference cites this paper.

When (not) to trust Monte Carlo approximations for hierarchical Bayesian inference Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-04T22:42:34.800057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4490e4bd-199b-4819-ba74-21ba8e9b6603 · inbound

An Implementation to Identify the Properties of Multiple Population of Gravitational Wave Sources cites this paper.

An Implementation to Identify the Properties of Multiple Population of Gravitational Wave Sources Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-18T17:06:39.517349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 43aae1bb-aae6-46b4-8e0a-04a4a188a390 · inbound

How do the LIGO-Virgo-KAGRA's Heavy Black Holes Form? No evidence for core-collapse Intermediate-mass black holes in GWTC-4 cites this paper.

How do the LIGO-Virgo-KAGRA's Heavy Black Holes Form? No evidence for core-collapse Intermediate-mass black holes in GWTC-4 Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning

Reference 180

Resolution: metadata mismatch; arxiv_id, observed 2026-05-08T23:14:23.406405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5fd3531a-b25f-4a32-a843-5d791d968d20 · inbound

End-to-End Population Inference from Gravitational-Wave Strain using Transformers cites this paper.

End-to-End Population Inference from Gravitational-Wave Strain using Transformers Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:02:05.995005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7c86ea5e-614c-4bab-a1fa-ebe979edf405 · inbound

Fortifying gravitational-wave population inference with normalizing flows cites this paper.

Fortifying gravitational-wave population inference with normalizing flows Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-02T11:36:04.238228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.