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Paper Citation Record · LEDGER

Uncertainty quantification for data-driven weather models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.13458.

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

pith.paper-citation-record.v1
2403.13458 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:30:07.110577Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T08:03:08.881697Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 275b7139-34e1-482f-ad86-415c81fb88ce · inbound

Diffusion-LAM: Probabilistic Limited Area Weather Forecasting with Diffusion cites this paper.

Diffusion-LAM: Probabilistic Limited Area Weather Forecasting with Diffusion Uncertainty quantification for data-driven weather models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T12:30:07.110577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T12:30:07.110577Z digest=sha256:e4dd4e21ac257eb9522fb1219492378233799663302456b1ce73609e54c15e0a

Observation c6d29956-c8bf-4a35-ac29-3f9cd0132927 · inbound

Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems cites this paper.

Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems Uncertainty quantification for data-driven weather models

Reference 108

Resolution
verified exact
arxiv_id, observed 2026-05-20T08:03:08.883852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T08:01:27.051916Z digest=sha256:1cccd7df93fcc6961c1f52c95a26cb7eb464fa7b5079629d70d7ef6ce32b031c