Paper Citation Record · LEDGER

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves

As of 7 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 1 inbound Pith citation observation for arXiv:2509.03816.

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

pith.paper-citation-record.v1
2509.03816 v1

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:43:15.961720Z

measured 72 of 72 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T16:23:03.448125Z

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

71 of 71 outbound references displayed

verified exact31
verified fuzzy4
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External citation measurements

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

Outbound references

Observation e67175f3-8729-4d43-b3f1-429ad9e4485d · outbound

This paper cites , Alexander, M J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Alexander, M J

Reference 1

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Observation b474dcad-b024-4ec2-a923-28b5952c4c2e · outbound

This paper cites \ Dunkerton, T J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves \ Dunkerton, T J

Reference 2

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Observation 6891503d-8906-4ecc-8c0d-cb29b1fa1e03 · outbound

This paper cites , Richter, J H.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Richter, J H

Reference 3

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Observation 43f93d71-479e-4397-a997-d02dd961c3a5 · outbound

This paper cites , Elafrou, A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Elafrou, A

Reference 4

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Observation 42637c9d-743a-4935-9d35-204432c1f24d · outbound

This paper cites APACrefauthors \ 2012 06.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves APACrefauthors \ 2012 06

Reference 5

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Observation 0a64aba8-d5ef-4585-8eb2-a01c24b668dd · outbound

This paper cites , Xie, L.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Xie, L

Reference 6

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Observation d7095cf6-bbf9-4f9a-9d21-32089400566d · outbound

This paper cites , Bruinsma, W P.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Bruinsma, W P

Reference 7

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Observation 941795c3-9b03-4d18-b31a-13200b08c582 · outbound

This paper cites , Gettelman, A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Gettelman, A

Reference 8

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Observation 9df52007-76a6-4bfe-9480-da2c31aee67f · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves On the Opportunities and Risks of Foundation Models

Reference 9

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Observation e7da732b-be53-4832-94a0-5fdccd70915c · outbound

This paper cites , Henn, B.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Henn, B

Reference 10

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Observation 4fbb11d2-56c8-4119-ac75-4312e736322f · outbound

This paper cites , Hatfield, S.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Hatfield, S

Reference 11

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Observation 6a97e697-3d1a-4538-ad19-91392fd7c24a · outbound

This paper cites \ Berner, J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves \ Berner, J

Reference 12

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Observation ef28ada8-4abe-4715-ab75-190e5f4b9962 · outbound

This paper cites , Kwon, H.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Kwon, H

Reference 13

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Observation 378d37d4-13f5-4430-9e9a-88c3b75f4665 · outbound

This paper cites \ Gerber, E P.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves \ Gerber, E P

Reference 14

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Observation 032211a9-efe9-41b4-ae00-52254ec72867 · outbound

This paper cites , Meng, F.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Meng, F

Reference 15

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Observation caebdcd6-7d1d-4e2b-93d2-8295dab544fd · outbound

This paper cites o rnbrack, A. , Leutbecher, M. , Kivi, R. \ Kyr \.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves o rnbrack, A. , Leutbecher, M. , Kivi, R. \ Kyr \

Reference 16

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Observation f388dade-ac8f-4591-bd1a-2da4d79fcf77 · outbound

This paper cites , Rhode, S.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Rhode, S

Reference 17

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Observation 24431cf2-2421-4026-873a-3012165407a4 · outbound

This paper cites , Sheshadri, A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Sheshadri, A

Reference 18

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Observation af29a3cc-fd56-4608-98ac-b2f8f0a4f1dd · outbound

This paper cites \ Alexander, M J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves \ Alexander, M J

Reference 19

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Observation 0fa6f396-beb1-4ac9-9f08-f57d48feb2fd · outbound

This paper cites , McCarty, W.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , McCarty, W

Reference 20

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Observation 62cbae0e-70ac-412d-8a34-a4ce599127e1 · outbound

This paper cites , Manzini, E.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Manzini, E

Reference 21

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Observation 9df45faf-bdbd-44c4-93d7-c0bbc9efaff4 · outbound

This paper cites , Horowitz, L W.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Horowitz, L W

Reference 22

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Observation 7677ee49-7445-481b-85e1-c36676c042fd · outbound

This paper cites , Birner, T.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Birner, T

Reference 23

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Observation 2c24fb5d-40af-4db4-9331-4a71fdda634a · outbound

This paper cites , Reichert, R.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Reichert, R

Reference 24

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Observation 0ce9326d-8712-4590-a325-0bdebb72aa93 · outbound

This paper cites , Sheshadri, A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Sheshadri, A

Reference 25

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Observation be8734fc-eb31-4ed5-ace2-c75513f4f609 · outbound

This paper cites Machine Learning Global Simulation of Nonlocal Gravity Wave Propagation.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves Machine Learning Global Simulation of Nonlocal Gravity Wave Propagation

Reference 26

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Observation 42ea59b7-1e73-4288-bf18-b9ae6c29e4db · outbound

This paper cites , Scaife, A A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Scaife, A A

Reference 27

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Observation a18ca8b4-88c3-4bf4-82ab-58f9f140bc1f · outbound

This paper cites u ndung der Theorie quadratischer Formen von unendlichvielen Ver \.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves u ndung der Theorie quadratischer Formen von unendlichvielen Ver \

Reference 28

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Observation 52234f17-c159-4f27-98ea-a01a64706b10 · outbound

This paper cites , Bell, B.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Bell, B

Reference 29

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Observation 5cc42219-671d-4cbf-bd85-4a9ec95847c2 · outbound

This paper cites , Bell, B.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Bell, B

Reference 30

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Observation 5c50c2d1-3ae2-4778-bf5d-c0c15f2bd1c0 · outbound

This paper cites , Wright, C J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Wright, C J

Reference 31

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Observation 40be5fe7-0da0-4e44-823b-3a56718e5f9a · outbound

This paper cites APACrefauthors \ 2024.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves APACrefauthors \ 2024

Reference 32

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Observation ab12a29e-d067-44e0-a7b1-9b2d64e6c551 · outbound

This paper cites , Spang, R.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Spang, R

Reference 33

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Observation a522e80c-e7d3-4799-91c5-9afc3cfee8c1 · outbound

This paper cites , Larsen, N.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Larsen, N

Reference 34

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Observation bacbe0b9-eb4d-41c5-8b4e-9e5547d8556c · outbound

This paper cites , Mlawer, E J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Mlawer, E J

Reference 35

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Observation dd5a5098-80de-4de1-b68d-43bcb94c530a · outbound

This paper cites Foundation Models for Generalist Geospatial Artificial Intelligence.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves Foundation Models for Generalist Geospatial Artificial Intelligence

Reference 36

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This paper cites \ Chun, H Y.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves \ Chun, H Y

Reference 37

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Observation 589b9d50-1d96-41d1-a873-8f2d48c12b0a · outbound

This paper cites , Green, B.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Green, B

Reference 38

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Observation 33fd598e-37d2-4d29-ba78-289781a3caaa · outbound

This paper cites , Alexander, M J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Alexander, M J

Reference 39

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Observation 06a0a963-4139-4a64-8a00-1074c7372bfd · outbound

This paper cites GraphCast: Learning skillful medium-range global weather forecasting.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves GraphCast: Learning skillful medium-range global weather forecasting

Reference 40

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Observation 2d6ae2c6-aaf3-4ab6-a3f7-8fc67a6d93c1 · outbound

This paper cites , Wright, C J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Wright, C J

Reference 41

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Observation deeb2f4d-1779-430f-ad4d-7074b4483483 · outbound

This paper cites , Calvin, K.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Calvin, K

Reference 42

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Observation 1c0e825a-a6a1-4b2b-8ce7-31df5ba1924a · outbound

This paper cites AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning

Reference 43

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Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves APACrefauthors \ 2015

Reference 44

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Observation 93d96f40-6ca1-4595-bc8b-243b64bece94 · outbound

This paper cites \ Miller, M J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves \ Miller, M J

Reference 45

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Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves Unresolved cited work

Reference 46

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Observation 27375408-5609-45b6-b3a8-8b756b9753e9 · outbound

This paper cites , Stevens, B.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Stevens, B

Reference 47

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Observation 0f1aabea-fa7f-498f-a331-884052db7424 · outbound

This paper cites , Shepherd, T G.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Shepherd, T G

Reference 48

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Observation c6c81961-fc36-4069-8f7a-c5a8216d0f2b · outbound

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Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves \ Lawrence, P

Reference 49

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.214439Z

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Observation bb2c09a0-4f2f-4b6a-b621-9f616da8412b · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves Attention U-Net: Learning Where to Look for the Pancreas

Reference 50

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Observation e28cca0b-a40f-4293-85b2-c3144dfaddbe · outbound

This paper cites , Wallace, J M.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Wallace, J M

Reference 51

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.183002Z

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Observation 209e1fdb-270f-4895-b3f0-8ac9bc7c4bdd · outbound

This paper cites , Shutts, G J.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Shutts, G J

Reference 52

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Observation a90705ee-7b4b-4732-a8df-b8f1f16884e4 · outbound

This paper cites , de la C \'a mara , A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , de la C \'a mara , A

Reference 53

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.169606Z

Source-reported events for the cited work

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Observation 47cf0966-203a-4b60-a6a3-11579da2e55f · outbound

This paper cites , van Niekerk, A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , van Niekerk, A

Reference 54

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.154894Z

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Observation 21d6097d-e044-4010-87cc-0120696e2eb8 · outbound

This paper cites , Wedi, N.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Wedi, N

Reference 55

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.139473Z

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

Observation d91c2143-61bb-436a-90a6-326b5e9fa415 · outbound

This paper cites , Sanchez-Gonzalez , A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Sanchez-Gonzalez , A

Reference 56

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Observation c71f7fb3-c2b8-4c82-913c-16d396ac8495 · outbound

This paper cites , Kruse, C G.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Kruse, C G

Reference 57

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.116630Z

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Observation 81a4c208-279d-4ea2-9840-9290a9aaa684 · outbound

This paper cites \ Gupta, A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves \ Gupta, A

Reference 58

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.102728Z

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Observation f25dbf30-3747-452f-b432-1a3e31ebf832 · outbound

This paper cites , KUMAR, ANKUR.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , KUMAR, ANKUR

Reference 59

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.088541Z

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

Observation 8609c980-d870-45aa-b39c-89001b81b0ad · outbound

This paper cites , Tateno, S.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Tateno, S

Reference 60

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.070404Z

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Observation e86599c0-56ed-4e53-9651-9c48e1997f45 · outbound

This paper cites Prithvi WxC: Foundation Model for Weather and Climate.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves Prithvi WxC: Foundation Model for Weather and Climate

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T10:43:15.919465Z

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Observation 5eb1a304-31ef-45fb-b247-5beea6e9848c · outbound

This paper cites , Strube, C.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Strube, C

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T10:43:15.923838Z

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Observation 920b47fa-4fc3-4c3e-ad2e-53c99c51e33b · outbound

This paper cites , Pahlavan, H A.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Pahlavan, H A

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-05T10:43:15.927747Z

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Observation daf822ba-597f-46f7-b1b8-e5bc61e6c4bc · outbound

This paper cites \ Chantry, M.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves \ Chantry, M

Reference 64

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T10:43:16.884484Z

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.

Observation 5cffd567-0e01-4237-8f1b-3bd9db7445cd · outbound

This paper cites MS-GWaM: A 3-dimensional transient gravity wave parametrization for atmospheric models.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves MS-GWaM: A 3-dimensional transient gravity wave parametrization for atmospheric models

Reference 65

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T10:43:16.767077Z

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.

Observation e923f9ad-2208-4bdd-a394-cc84b259ee55 · outbound

This paper cites , Zhang, F.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Zhang, F

Reference 66

Resolution: verified exact; doi, observed 2026-08-05T10:43:16.030523Z

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.

Observation 02638099-6a14-4205-9fa4-aa44ddc306da · outbound

This paper cites , Miao, C.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Miao, C

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-05T10:43:15.944220Z

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Observation 28323433-0cc5-4aac-813d-c7ed4b242beb · outbound

This paper cites , Tomikawa, Y.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Tomikawa, Y

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-05T10:43:15.948663Z

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Observation 1abab0ee-aece-42ff-a8fd-e345651b0dfa · outbound

This paper cites , Golaz, J C.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves , Golaz, J C

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-05T10:43:15.952776Z

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Observation 667831e3-54e5-43e1-b7fb-c72befc284d8 · outbound

This paper cites write newline.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves write newline

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:43:16.914864Z

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.

Observation 73680362-55e9-4d92-b292-6c3208d6f073 · outbound

This paper cites write newline.

Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves write newline

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:43:16.899711Z

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

Pith citing papers

Observation 8a3667fb-15dc-40a0-a6e5-9b4d00cdc99a · inbound

Interpretable Neural Networks to Predict Momentum Fluxes of Orographic Gravity Waves cites this paper.

Interpretable Neural Networks to Predict Momentum Fluxes of Orographic Gravity Waves Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-08T20:24:08.720224Z

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.