Paper Citation Record · LEDGER

A Deep Learning Model of Lightning Stroke Density

As of 23 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2509.10399.

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

pith.paper-citation-record.v1
2509.10399 v1

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:59:36.130135Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

10 of 10 outbound references displayed

verified exact0
verified fuzzy0
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bc50bda6-9fed-402f-9cd4-25ac527085e6 · outbound

This paper cites Thornton 1 , Chris J.

A Deep Learning Model of Lightning Stroke Density Thornton 1 , Chris J

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:35.209834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df01ca49-8a64-47c4-8411-9848803f6a44 · outbound

This paper cites an unresolved cited work.

A Deep Learning Model of Lightning Stroke Density Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:35.924507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28d7620d-406e-4902-bb04-8261b6c17397 · outbound

This paper cites Stolz et al.

A Deep Learning Model of Lightning Stroke Density Stolz et al

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:35.684632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6076528-8ca5-463c-b50d-0e9982a5c326 · outbound

This paper cites latitudexlongitude°.

A Deep Learning Model of Lightning Stroke Density latitudexlongitude°

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:35.807732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03f1d2f8-4aca-4d7a-86e0-86194dcda39b · outbound

This paper cites an unresolved cited work.

A Deep Learning Model of Lightning Stroke Density Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:36.001361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1661141b-3754-4ff3-9eac-b577e46903b3 · outbound

This paper cites There are sharp gradients in the lightning stroke density over Brazil, which are not replicated by the R14 parameterization or the CNN models.

A Deep Learning Model of Lightning Stroke Density There are sharp gradients in the lightning stroke density over Brazil, which are not replicated by the R14 parameterization or the CNN models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:36.057210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe3fb155-a5be-4eb0-a6c1-f89160cb7ded · outbound

This paper cites However, Romps et al.

A Deep Learning Model of Lightning Stroke Density However, Romps et al

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:35.608500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ed38f4f-a22b-4bf9-b39b-4d3d4cf3c351 · outbound

This paper cites Additionally, with the inclusion of geographic variables, such as coast and terrain, the logistic regression method accurately predicted lightning occurrence 86% of the time.

A Deep Learning Model of Lightning Stroke Density Additionally, with the inclusion of geographic variables, such as coast and terrain, the logistic regression method accurately predicted lightning occurrence 86% of the time

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:35.734686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbb8e766-4b72-4498-b419-9a0f5443512f · outbound

This paper cites an unresolved cited work.

A Deep Learning Model of Lightning Stroke Density Unresolved cited work

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:35.330438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6f799f5-e9b6-4f19-b375-a2820229483a · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

A Deep Learning Model of Lightning Stroke Density U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 4289

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:36.130135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.