Paper Citation Record · LEDGER

Learning from nature: insights into GraphDOP's representations of the Earth System

As of 18 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 3 inbound Pith citation observations for arXiv:2508.18018.

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

pith.paper-citation-record.v1
2508.18018 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:42:53.092732Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T03:05:31.628251Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

21 of 21 outbound references displayed

verified exact1
verified fuzzy0
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation ccf2253d-2e8e-4ca2-b1a2-5a45517ef557 · outbound

This paper cites Massimo Bonavita.

Learning from nature: insights into GraphDOP's representations of the Earth System Massimo Bonavita

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.676664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f741de1-d0e8-42eb-9f1a-2f6a59045e5a · outbound

This paper cites URL https://agupubs.onlinelibrary.

Learning from nature: insights into GraphDOP's representations of the Earth System URL https://agupubs.onlinelibrary

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.686624Z

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Observation 6f3c7a56-1325-433b-b9d8-8f937922babe · outbound

This paper cites URL https://doi.org/10.1002/qj.3803.

Learning from nature: insights into GraphDOP's representations of the Earth System URL https://doi.org/10.1002/qj.3803

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.787035Z

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Observation 1147aed3-f241-49e0-97c7-3f71eff18d28 · outbound

This paper cites The Platonic Representation Hypothesis.

Learning from nature: insights into GraphDOP's representations of the Earth System The Platonic Representation Hypothesis

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.799196Z

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Observation 47b998cd-bb2d-437a-b2a6-87dce86e9580 · outbound

This paper cites AIFS -- ECMWF's data-driven forecasting system.

Learning from nature: insights into GraphDOP's representations of the Earth System AIFS -- ECMWF's data-driven forecasting system

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.822678Z

Source-reported events for the cited work

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Observation f96fa214-724a-4b21-b715-99794fc258de · outbound

This paper cites an unresolved cited work.

Learning from nature: insights into GraphDOP's representations of the Earth System Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-05T16:42:53.972097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 55513231-1916-4765-908b-a28af75aab42 · outbound

This paper cites Data driven weather forecasts trained and initialised directly from observations.

Learning from nature: insights into GraphDOP's representations of the Earth System Data driven weather forecasts trained and initialised directly from observations

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.850183Z

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Observation 7b6cbf2e-1135-4734-bdfb-a31e720c6a43 · outbound

This paper cites URL https://doi.org/10.1038/s41586-024-08252-9.

Learning from nature: insights into GraphDOP's representations of the Earth System URL https://doi.org/10.1038/s41586-024-08252-9

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.859871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00be3478-aeba-4fba-9e2d-31e309ef931e · outbound

This paper cites URL https://doi.org/10.1002/qj.5002.

Learning from nature: insights into GraphDOP's representations of the Earth System URL https://doi.org/10.1002/qj.5002

Reference 19

Resolution: verified exact; doi, observed 2026-08-05T16:42:53.257301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0223e704-5fcc-47a2-96d1-ece3aa7e76e7 · outbound

This paper cites Chang, Ashesh Rambachan, and Sendhil Mullainathan.

Learning from nature: insights into GraphDOP's representations of the Earth System Chang, Ashesh Rambachan, and Sendhil Mullainathan

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.914087Z

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Unavailable: canonical work link unavailable.

Observation c3410170-108a-4e7b-89d2-afb17c7d3671 · outbound

This paper cites URL https://arxiv.org/abs/2507.06952.

Learning from nature: insights into GraphDOP's representations of the Earth System URL https://arxiv.org/abs/2507.06952

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.957376Z

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Unavailable: canonical work link unavailable.

Observation 74b699e5-485f-48b2-bd70-75436a323602 · outbound

This paper cites Neural general circulation models optimized to predict satellite-based precipitation observations.

Learning from nature: insights into GraphDOP's representations of the Earth System Neural general circulation models optimized to predict satellite-based precipitation observations

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:53.092732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0f667f7-5cb8-4e32-ad7c-3c79ce0a2565 · outbound

This paper cites Lewis Fry Richardson.

Learning from nature: insights into GraphDOP's representations of the Earth System Lewis Fry Richardson

Reference 2000

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.874238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91b1077d-790f-47a3-8610-0d36183b0b67 · outbound

This paper cites Data driven weather forecasts trained and initialised directly from observations.

Learning from nature: insights into GraphDOP's representations of the Earth System Data driven weather forecasts trained and initialised directly from observations

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.841087Z

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Observation 95d1502a-6eee-4af4-b7a1-09457e315f95 · outbound

This paper cites URL https: //a.tellusjournals.se/articles/10.1080/16000870.2016.1272779.

Learning from nature: insights into GraphDOP's representations of the Earth System URL https: //a.tellusjournals.se/articles/10.1080/16000870.2016.1272779

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.699537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c202e5c8-6fb3-4330-89a5-c6dca011d6db · outbound

This paper cites World Models.

Learning from nature: insights into GraphDOP's representations of the Earth System World Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.744766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2d71fcb-fdbe-4b5d-b76c-f2757fae68a5 · outbound

This paper cites Dream to Control: Learning Behaviors by Latent Imagination.

Learning from nature: insights into GraphDOP's representations of the Earth System Dream to Control: Learning Behaviors by Latent Imagination

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.772621Z

Source-reported events for the cited work

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Observation 8d75b532-b760-421a-b3b0-751f4702c825 · outbound

This paper cites Forecasting Global Weather with Graph Neural Networks.

Learning from nature: insights into GraphDOP's representations of the Earth System Forecasting Global Weather with Graph Neural Networks

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.809714Z

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Observation fa0fd843-419a-49a9-bb99-714606b5329d · outbound

This paper cites Deep Learning for Day Forecasts from Sparse Observations.

Learning from nature: insights into GraphDOP's representations of the Earth System Deep Learning for Day Forecasts from Sparse Observations

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.671978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c19783b-52b1-476c-83de-5ff87850ff41 · outbound

This paper cites GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations.

Learning from nature: insights into GraphDOP's representations of the Earth System GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.659993Z

Source-reported events for the cited work

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Observation 918caed5-9805-4c0b-8343-621d7df69032 · outbound

This paper cites Deep Learning for Day Forecasts from Sparse Observations.

Learning from nature: insights into GraphDOP's representations of the Earth System Deep Learning for Day Forecasts from Sparse Observations

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.664119Z

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Pith citing papers

Observation b88b72eb-c456-447e-b61d-a4607cadbb50 · inbound

AIFS-DOP: End-to-End Medium-Range Weather Prediction from Observations Alone with Machine Learning cites this paper.

AIFS-DOP: End-to-End Medium-Range Weather Prediction from Observations Alone with Machine Learning Learning from nature: insights into GraphDOP's representations of the Earth System

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T18:59:43.838027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8adfd3e5-f9b0-483a-adef-e0ecd12fdb1e · inbound

Global reanalysis from observations alone with machine learning cites this paper.

Global reanalysis from observations alone with machine learning Learning from nature: insights into GraphDOP's representations of the Earth System

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-07-10T16:17:21.539290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 89f15c56-345a-4c7e-9810-cfe5f68356cf · inbound

OCELOT: Direct Atmospheric Forecasting from Heterogeneous Earth Observations Using a Graph-Transformer Hybrid Model cites this paper.

OCELOT: Direct Atmospheric Forecasting from Heterogeneous Earth Observations Using a Graph-Transformer Hybrid Model Learning from nature: insights into GraphDOP's representations of the Earth System

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T03:05:31.628251Z

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