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Paper Citation Record · LEDGER

ParamANN: A Neural Network to Estimate Cosmological Parameters for $\Lambda$CDM Universe Using Hubble Measurements

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2309.15179.

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

pith.paper-citation-record.v1
2309.15179 v3

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 2026-08-11T22:21:35.060842Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:54:19.782894Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • 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 15fd08f3-2e19-45fb-9600-02381d1d2643 · inbound

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

Learning from galactic rotation curves: a neural network approach ParamANN: A Neural Network to Estimate Cosmological Parameters for $\Lambda$CDM Universe Using Hubble Measurements

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T22:21:35.060842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:21:35.060842Z digest=sha256:52fadf8cabd8377f8f815de4631253de2f984ddbb45502bde677b83872735d5a

Observation bcbb9ae3-a9b2-44ea-877a-843d8e9cc152 · inbound

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR cites this paper.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR ParamANN: A Neural Network to Estimate Cosmological Parameters for $\Lambda$CDM Universe Using Hubble Measurements

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:54:19.884383Z

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=2026-08-07T14:54:17.725282Z digest=sha256:62963c49e133274d89ae69df2a8e1375b2f9174099cf6e9f536e7df0a8bcab8d