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Paper Citation Record · LEDGER

ArchesWeather: An efficient AI weather forecasting model at 1.5{\deg} resolution

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.14527.

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

pith.paper-citation-record.v1
2405.14527 v2

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 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:35:21.787544Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 31080582-a2fb-4378-b109-f96d34119308 · inbound

Deep Learning Weather Models for Subregional Ocean Forecasting: A Case Study on the Canary Current Upwelling System cites this paper.

Deep Learning Weather Models for Subregional Ocean Forecasting: A Case Study on the Canary Current Upwelling System ArchesWeather: An efficient AI weather forecasting model at 1.5{\deg} resolution

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:21.787544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:21.787544Z digest=sha256:e233c63e60b96472a4fa93d6916576450be086840da1e89293128b846cf8c6cc

Observation c0863f3a-014c-4efd-90e2-a2c65d63bb51 · inbound

Modernizing CNN-based Weather Forecast Model towards Higher Computational Efficiency cites this paper.

Modernizing CNN-based Weather Forecast Model towards Higher Computational Efficiency ArchesWeather: An efficient AI weather forecasting model at 1.5{\deg} resolution

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T17:29:30.528283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:29:30.528283Z digest=sha256:1b7a956fc32061cfb86c4ed4def11e10421ed81107e29881ecc6c0df37c6d148

Observation 578dac14-b551-4515-af63-7765807a03c3 · inbound

PINN-Cast: Exploring the Role of Continuous-Depth NODE in Transformers and Physics Informed Loss as Soft Physical Constraints in Short-term Weather Forecasting cites this paper.

PINN-Cast: Exploring the Role of Continuous-Depth NODE in Transformers and Physics Informed Loss as Soft Physical Constraints in Short-term Weather Forecasting ArchesWeather: An efficient AI weather forecasting model at 1.5{\deg} resolution

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T09:36:27.614564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T10:05:51.493709Z digest=sha256:da4f9b28d5ccf092e32ddb57917ea31fb1ecdab581ff4bbb26f86bac6a453ef1

Observation e09491fd-34c7-48c4-a699-4a0dcc34a738 · inbound

The physics of AI weather models cites this paper.

The physics of AI weather models ArchesWeather: An efficient AI weather forecasting model at 1.5{\deg} resolution

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-25T02:25:14.337995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-25T02:20:39.109304Z digest=sha256:cb97f57dd5164da53f01b22cc19c10760e54bc8df48bceb5973d295ab5974693

Observation c543d4ee-6c01-426b-954d-89817a1692a1 · inbound

PhysMetrics.Weather: An Evaluation Framework for Physical Consistency in ML Weather Models cites this paper.

PhysMetrics.Weather: An Evaluation Framework for Physical Consistency in ML Weather Models ArchesWeather: An efficient AI weather forecasting model at 1.5{\deg} resolution

Reference 43

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T04:27:37.271780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T13:52:47.249619Z digest=sha256:2ff72fec799ae1ac063d768b2c659e4d284f94e4dd532356696858dd4ea9b437