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Paper Citation Record · LEDGER

Distinguishing thermal histories of dark matter from structure formation

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.00065.

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

pith.paper-citation-record.v1
2306.00065 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:52:45.506414Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:28:38.627048Z

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 05dcff43-7a76-44ba-a8b8-1fe90e4f52b6 · inbound

Prospects for high-resolution probes of galaxy dynamics tracing background cosmology in MaNGA cites this paper.

Prospects for high-resolution probes of galaxy dynamics tracing background cosmology in MaNGA Distinguishing thermal histories of dark matter from structure formation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T17:52:45.506414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:52:45.506414Z digest=sha256:57c22c29eb1c222cf6941dda130ec28dad33efd27a030c7e04ae0180ba1b4cf1

Observation 7a0ab493-2aa6-4448-aeba-f4836514f9d7 · inbound

Machine Learning Does It and Does It Better: Unearthing Primordial Dark-Matter Velocities from the Matter Power Spectrum cites this paper.

Machine Learning Does It and Does It Better: Unearthing Primordial Dark-Matter Velocities from the Matter Power Spectrum Distinguishing thermal histories of dark matter from structure formation

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:28:38.628307Z

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=2026-06-27T05:48:47.779139Z digest=sha256:e5f993526bdced3d4a1689db6472eec3c80a7d99e3f65f6f040abbacdff080e8