Paper Citation Record · LEDGER

Spatial Modeling and Risk Zoning of Global Extreme Precipitation via Graph Neural Networks and r-Pareto Processes

As of 9 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 0 inbound Pith citation observations for arXiv:2509.10362.

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

pith.paper-citation-record.v1
2509.10362 v1

Coverage vector

measured 6 of 6 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:54:54.289758Z

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

6 of 6 outbound references displayed

verified exact0
verified fuzzy0
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a8ae81aa-fb67-423c-8f03-329012e18d59 · outbound

This paper cites Graph Neural Networks for Enhancing Ensemble Forecasts of Extreme Rainfall.

Spatial Modeling and Risk Zoning of Global Extreme Precipitation via Graph Neural Networks and r-Pareto Processes Graph Neural Networks for Enhancing Ensemble Forecasts of Extreme Rainfall

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T17:54:53.906790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 117e9cf8-3a26-44a2-8741-61303b951166 · outbound

This paper cites Organization and environmental properties of extreme-rain- producing mesoscale convective systems.

Spatial Modeling and Risk Zoning of Global Extreme Precipitation via Graph Neural Networks and r-Pareto Processes Organization and environmental properties of extreme-rain- producing mesoscale convective systems

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T17:54:54.139195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e210976f-7a7b-40a8-86db-19ed3b00bc50 · outbound

This paper cites Neural Networks for Geospatial Data.

Spatial Modeling and Risk Zoning of Global Extreme Precipitation via Graph Neural Networks and r-Pareto Processes Neural Networks for Geospatial Data

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T17:54:54.289758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f79b96ed-4ce8-495d-a282-109c48570c03 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Spatial Modeling and Risk Zoning of Global Extreme Precipitation via Graph Neural Networks and r-Pareto Processes Semi-Supervised Classification with Graph Convolutional Networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T17:54:54.008287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d645b2f7-ec45-4fc4-afd8-fa6f54ffa84e · outbound

This paper cites Relationships between precipitation and surface temperature.

Spatial Modeling and Risk Zoning of Global Extreme Precipitation via Graph Neural Networks and r-Pareto Processes Relationships between precipitation and surface temperature

Reference 386

Resolution: unresolved; no resolver link, observed 2026-08-04T17:54:54.241441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b44d289c-d0fc-45eb-ae4e-c0e61479b6de · outbound

This paper cites Extremes in High Dimensions: Methods and Scalable Algorithms.

Spatial Modeling and Risk Zoning of Global Extreme Precipitation via Graph Neural Networks and r-Pareto Processes Extremes in High Dimensions: Methods and Scalable Algorithms

Reference 1421

Resolution: unresolved; no resolver link, observed 2026-08-04T17:54:54.074802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.