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Paper Citation Record · LEDGER

Effective cosmic density field reconstruction with convolutional neural network

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2306.10538.

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

pith.paper-citation-record.v1
2306.10538 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:54:06.382311Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T00:31:19.422201Z

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 939f7a6a-17fe-4192-b72e-690e2c87b238 · inbound

Probing primordial non-Gaussianity by reconstructing the initial conditions cites this paper.

Probing primordial non-Gaussianity by reconstructing the initial conditions Effective cosmic density field reconstruction with convolutional neural network

Reference 59

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unresolved
no resolver link, observed 2026-08-12T04:54:06.382311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:54:06.382311Z digest=sha256:468fc5912978b9b446669e6ad6cb297c09f506f8eb041f840edca74724084ef8

Observation 1cd9a077-7481-47fe-8bc8-accd1a748683 · inbound

Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation cites this paper.

Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation Effective cosmic density field reconstruction with convolutional neural network

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-03T23:38:16.512394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:38:16.512394Z digest=sha256:5b370df6c8c5fc26920e170c9d89b187832ff7cf40616da5885e10965ead82dc

Observation 16e4a4a7-63cc-448f-be0c-17c2697b9977 · inbound

The Linear Point Standard Ruler with DESI DR1 and DR2 Data cites this paper.

The Linear Point Standard Ruler with DESI DR1 and DR2 Data Effective cosmic density field reconstruction with convolutional neural network

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-04T06:27:21.951729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:27:21.951729Z digest=sha256:6bc09db00b4a566b636d69a2a8dad5416a35264df30288af63e6835ec1d01188

Observation c9c3501d-81d6-4a2f-976b-886de237e49b · inbound

On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods cites this paper.

On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods Effective cosmic density field reconstruction with convolutional neural network

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-12T00:31:19.426083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-07T15:04:42.546535Z digest=sha256:4baed1e84da4e1d5b965b3c1b3c2597f10812d3b17367773a6d40eec10b82483

Observation d7dc32f3-3cc2-4232-bf66-8370bde9ff97 · inbound

Standard Reconstruction Shifts the Optimal Input Scale for CNN-Based Density-Field Reconstruction cites this paper.

Standard Reconstruction Shifts the Optimal Input Scale for CNN-Based Density-Field Reconstruction Effective cosmic density field reconstruction with convolutional neural network

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-01T22:12:37.125654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T22:12:37.125654Z digest=sha256:6cd801b984fe6e14667c1646c577c6c8dae30366ffb0b918276de8d0befa07d5