{"as_of":"2026-08-18T08:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3b3ad250ee78a288c5525b10de790bc38a7f032e7bf831ad28b071e886bdc884","coverage":[{"denominator":40,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":40,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-13T05:25:47.083510Z","state":"measured"},{"denominator":40,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":40,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.08969/citation-record","integrity":"/paper/2607.08969/integrity","json":"/paper/2607.08969/citation-record.json","paper":"/paper/2607.08969"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1051/0004-6361/202346765","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"V., & Carlsson, M","venue":"Astronomy and Astrophysics","work_id":"c150488c-1ae8-4a78-ae07-4cd3cd10eb7d","year":2023},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:06ebdf941563c11e333635b97bf22648f5713b7fb1ce3f06c2c57a6ddad7cee3","observation_id":"294c97f1-bca4-41fc-8462-a0371cccf374","resolution":{"observed_at":"2026-07-13T05:29:22.236711Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:28.800385+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:28.800385+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2010, Astronomische Nachrichten, 331, 636, doi: 10.1002/asna.201011390","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:051662ad1a73aaa9e55e21ebd3c1d4c1088de33997cde7d356ecf18a05c769d1","observation_id":"a48e586f-8f72-447c-9116-d73c48ccbda4","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-319-27104-0","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"J., & Zwinderman, A","venue":null,"work_id":"82b188ca-b742-4551-9768-17d1ad670353","year":2016},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:654984ac34db648a6440f6471871239cb6de063baa378110004ae8f8132d03b7","observation_id":"7099c2d0-934b-4c6f-9e67-7a9567af858d","resolution":{"observed_at":"2026-07-13T05:29:22.285529Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:29.290662+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:29.290662+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1136/bmj.j3683","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"J., & Altman, D","venue":"BMJ","work_id":"6a7e501a-9a07-488b-ac00-5a4a032a9ee4","year":2017},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:0d95a0ebb8e11908ef2f96452792b0f63f2a49e22a8f060f1017633b89b92c84","observation_id":"c31f6d54-441a-4997-adec-beaa33968462","resolution":{"observed_at":"2026-07-13T05:29:22.311755Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:29.537677+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:29.537677+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":null,"venue":null,"work_id":null,"year":1991},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:b55b1332283e42b02037e9181922a35155d2c040453cef4c7bafc138af0ca34f","observation_id":"fed06603-def6-4737-a6d4-38f643aa03e5","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"V., Carlsson, M., Hansteen, V","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:570024d6bf1d8812f780ff98b2a7bc308b400f6ff48244b5c15d8c760dd40309","observation_id":"ab10d8a9-3a15-4284-aae5-f5302ff48919","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"R., Millman, K","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:e012bbade743e3664bc9c161d2af93aa5836d42a6ed9b0c31c5814d7efe3a323","observation_id":"4d55d1fd-813c-4569-8fca-f834df7fd671","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2015, in Proceedings of the IEEE International Conference on Computer Vision (ICCV), 1026–1034, doi: 10.1109/ICCV.2015.123","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:8d4af1cc59e3f7a3355a37504e3cb1fca0b08c45d32aa82ab4a643731f3ea780","observation_id":"2e0f1a8d-787b-4b78-a29e-6072408a7c2a","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2016, in Proceedings of the IEEE conference on computer vision and pattern recognition, 770–778, doi: 10.1109/CVPR.2016.90","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:e702692d808ddbc1ad06fa99d9e1457354a9631abcd417dc8042158e977ca53b","observation_id":"9f2f7eb5-2226-4dcc-addb-52a6cedb1bea","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":null,"venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:29146a87603cabace6598933a517268b84ed5b8ec6c1b4a58cd60511f8affaa7","observation_id":"76259733-60f4-4294-9cef-a9d1321a88a5","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1086/592042","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"The Astrophysical Journal","work_id":"4cc462f0-9949-4081-9e04-7b450492fec0","year":2008},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:b57866ea3a8028dd7cb554094b5b3eae987b45517f5122af3e53af5f34cfdd4f","observation_id":"5a1b1e78-2e86-4732-938f-3020545b2aa9","resolution":{"observed_at":"2026-07-13T05:29:22.242615Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:30.327809+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:30.327809+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"I., Huang, C., Sitdikov, I., et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:e1d918a07a3e233cc011bbc91c4c19a93a76df17e7c842d7ac0ed2b65b7ba95c","observation_id":"e252fd51-1dd0-452e-a689-837ca2d627d0","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1175/mwr-d-21-0217.1","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"2022, Monthly Weather Review, 150, 2279 , doi: 10.1175/MWR-D-21-0217.1","venue":"Monthly Weather Review","work_id":"2deca2ee-5121-4b2d-b3fd-ef8674e19a84","year":2022},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:6466d0bd852122f82226b7c28c52c59dc9e3f49ef1e86636e0b04a1f26057ede","observation_id":"2f8f1b51-6588-4f02-862d-57360adf1fe1","resolution":{"observed_at":"2026-07-13T05:29:22.252195Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:30.874541+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:30.874541+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/pasj/psu114","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Publications of the Astronomical Society of Japan","work_id":"84b6a697-7dcf-49d9-ae6d-f7cd0e2edca4","year":2014},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:58b0134938740e5594a669015f3928eaa252f92c75f5960ad6257587ead1757e","observation_id":"6665ac74-3502-4db5-84ab-dce2d5e7918d","resolution":{"observed_at":"2026-07-13T05:29:22.232419Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:31.129189+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:31.129189+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1088/0031-8949/2013/t155/014025","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"N., Abramenko, V","venue":"Physica Scripta","work_id":"207a139d-ad53-48a6-be0d-5b9e33985fb7","year":2013},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:bbd6e712f095c53acd6b4633ca04ef71ab52fd791c91947e64f9863cf91cc709","observation_id":"4abbd419-4753-4d2f-bc05-895d800ef873","resolution":{"observed_at":"2026-07-13T05:29:22.216211Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:31.388045+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:31.388045+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1088/0004-637x/808/1/59","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"N., Couvidat, S., & Lagg, A","venue":"The Astrophysical Journal","work_id":"8d129dd2-0ce7-4195-9aa0-3c263b5db123","year":2015},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:aaaf9ad2834156f16566e4d55b69665402f07256dddd44aedfa2728ff72c3632","observation_id":"da74f9bc-199f-4a0e-80b5-f91ef9813e7e","resolution":{"observed_at":"2026-07-13T05:29:22.203636Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:31.636738+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:31.636738+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11207-010-9679-0","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"N., Kosovichev, A","venue":"Solar Physics","work_id":"e45db52a-9180-411c-9576-df24f2c15db9","year":2011},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:e9759502745b6029f497d42674f052df23ba6e01d9d1fb1c69e5fe82eeee8c13","observation_id":"5c5f3a3c-84de-41fe-aea7-1624913d259c","resolution":{"observed_at":"2026-07-13T05:29:22.208928Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:31.895391+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:31.895391+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/mnras/stac2946","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"M., & Guerrero, G","venue":"Monthly Notices of the Royal Astronomical Society","work_id":"050a18e6-ced8-40fc-8934-202f0e72c9a1","year":2023},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:93a4046f5ede2f127a48ea20ce3e73bcbabec6c472e7f9607ff04f368e2ba8c7","observation_id":"07862680-cd76-4efd-9a3d-6674caf13e5b","resolution":{"observed_at":"2026-07-13T05:29:22.299532Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:32.20967+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:32.20967+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"L., Hannun, A","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:37704ffbe11b7dc646b392239273bc9e9daee80f361c5b83947d501ba1cd68d5","observation_id":"c7108bcc-03fb-4376-b9ae-67088443f4ea","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"S., & Cabot, W","venue":null,"work_id":null,"year":1994},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:699d9b6286bde43dfa0fd176bb85e153cadbbfa363009fc2e75ed6780d0f5441","observation_id":"47cedb36-f4b3-4167-bdda-ba30beccb9bb","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1051/0004-6361/202243439","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"2022, Astronomy & Astrophysics, 663, A96, doi: 10.1051/0004-6361/202243439","venue":"Astronomy and Astrophysics","work_id":"b534a76e-28c1-47d7-b189-dd7c8d1dbde8","year":2022},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:b70cec80940c16bb0f9b78ac92a4f03c97ef81a0ca09c34ae677e4f1d0f94629","observation_id":"6d377e41-c40f-4593-bdc7-23658d565b8f","resolution":{"observed_at":"2026-07-13T05:29:22.272957Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:32.46224+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:32.46224+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/bf00158429","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"1985, Solar Physics, 100, 209, doi: 10.1007/BF00158429","venue":"Solar Physics","work_id":"3cfa33e6-cf3c-40fc-8527-15f02b72296e","year":1985},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:707ee35634ff575730fb4fe43dcb47ec93c17078bd12cd771a25b3780a893b0a","observation_id":"9ff0bfdf-2d4c-4fda-ba8d-a8086f12477b","resolution":{"observed_at":"2026-07-13T05:29:22.251448Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:32.779086+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:32.779086+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/s1081-1206(10)60595-9","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"D., & Marshall, G","venue":"Annals of Allergy Asthma & Immunology","work_id":"f445c43a-bfd5-421a-9116-79276aefc15f","year":2008},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:94c2ff554f495b9442c3683f34341b532e473b40cb4bf51f9806a9ee4c138cb3","observation_id":"90903948-aa4f-4e0e-8e27-9e9fcc23df45","resolution":{"observed_at":"2026-07-13T05:29:22.313224Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:33.025659+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:33.025659+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.07043","last_updated":"2021-11-13T05:29:20Z","snapshot_observed_at":"2026-08-16T17:42:08.273087Z","submitted_at":"2021-11-13T05:29:20Z","title":"Reynolds Stress Modeling Using Data Driven Machine Learning Algorithms","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.07043","snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"cited_paper":"/paper/2111.07043","citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:a2523cc782739125e0046646d2f8e0b71a7e90495049851175859810e4ee90f5","observation_id":"b55edfe6-03b4-498d-a985-055d63595a0c","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.01703","last_updated":"2019-12-03T22:06:05Z","snapshot_observed_at":"2026-07-06T08:41:49.632205Z","submitted_at":"2019-12-03T22:06:05Z","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.01703","snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2019, PyTorch: An Imperative Style, High-Performance Deep Learning Library, doi: 10.48550/arXiv.1912.01703","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"cited_paper":"/paper/1912.01703","citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:3b6a300150ee2eff183ba7f49cedc1356b5020a7b5c12642be55f898c5e0280c","observation_id":"7b454eb0-5ae5-4c05-813d-557218709c04","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2011, Journal of Machine Learning Research, 12, 2825, doi: 10.5555/1953048.2078195","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:e759c22add5844f5daaed73d8bc8a1310bfc334619241d8bb6970887ca857304","observation_id":"778f54af-6b3d-477e-a30c-7c3da9a09e8f","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2020, pandas-dev/pandas: Pandas, doi: 10.5281/zenodo.3509134","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:b4e1ed68fbaf6f51c59f015c2e8a104abf955c085d16c46f0df9981987a9febf","observation_id":"77b64bc0-4b28-4ea8-862a-82d74159ac79","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2018, The Astrophysical Journal, 859, 161, doi: 10.3847/1538-4357/aabba0","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:9a998ccf7584f936038b444470752d2b0413389549a3e4b90a28f2d879bfea03","observation_id":"c7ab74af-bdb3-4092-a20d-5c163f43e2ff","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"R., Warner, M., Keil, S","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:d8d2f567587dd71721ac9be8b1620280679bc51e3c74edf220a672daae105021","observation_id":"5cfd2423-450f-43a5-a1a3-6dcdebb857e1","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3847/1538-4357/abd9c7","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"M., Kitiashvili, I","venue":"The Astrophysical Journal","work_id":"2c512127-aed6-49bd-be97-f19768bd6456","year":2021},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:bd7bda87bee08e477d4a136dd32b85e4df7546d8280cc17d8dc7a823f041df1b","observation_id":"4d7acdf2-5029-4522-928b-39e5787622ef","resolution":{"observed_at":"2026-07-13T05:29:22.277395Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:34.572462+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:34.572462+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-08-17T19:17:06.411141Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2015, in ICLR, doi: 10.48550/arXiv.1409.1556","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:15c3fc59b09fa8280f7af7aee82f40b85be3da51d50a8df1a8b1277d71038966","observation_id":"38b56560-0a77-4437-9cff-c1916e5d76e2","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"1963, Monthly Weather Review, 91, 99, doi: 10.1175/1520-0493(1963)091⟨0099: GCEWTP⟩2.3.CO;2","venue":null,"work_id":null,"year":1963},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:28575715c981dd969c5bbfc76358ddb2c564d056ea268706c120a77f160ced49","observation_id":"69278b30-331b-4b83-b79b-647f91a84988","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"F., & Nordlund, ˚A","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:5f20b2848353bc6f1c150d507c07266cde0567d68249fb78b6197a75aa296715","observation_id":"f3d5242c-fd36-465a-a43f-482f9eb591ed","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2020, Nature Methods, 17, 261, doi: 10.1038/s41592-019-0686-2 V¨ ogler, A., Shelyag, S., Sch¨ ussler, M., et al","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:1bd6bac65f170b5f31d397723b0afada4d883449e1c75260eca8dace124f0d17","observation_id":"51c637aa-e185-4a35-a9b4-12b2f147c7ec","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:211b02dc0fff4ac8c830cd372baec0bd5618ced2741c79ab940fd750c291d192","observation_id":"8d8c73e3-bb01-4929-9939-066f13a5fee2","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/app10051897","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"2020, Applied Sciences, 10, doi: 10.3390/app10051897","venue":"Applied Sciences","work_id":"ad26a652-eb80-429c-a26e-9725fb780874","year":2020},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:2979bd038dd3eae967171c2b1690923ce0a60f105b49d9dc0144dc587613df60","observation_id":"c65ca148-83b6-4ac1-a3d4-210b92e29705","resolution":{"observed_at":"2026-07-13T05:29:22.204498Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:35.660012+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:35.660012+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1507.07999","last_updated":"2015-07-29T01:24:45Z","snapshot_observed_at":"2026-08-17T02:51:23.666118Z","submitted_at":"2015-07-29T01:24:45Z","title":"Simulations of Stellar Magnetoconvection using the Radiative MHD Code `StellarBox'","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1507.07999","snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"N., & Kosovichev, A","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"cited_paper":"/paper/1507.07999","citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:0cb9cf0d1b0f2b6acf281c3bea609bd0bfcfce9b437a72a8595a0f1c62702713","observation_id":"fb4351e4-3c27-43b0-b891-35f7d32bb165","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1051/978-2-7598-2196-9.c004","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"N., & Kosovichev, A","venue":null,"work_id":"7a10d79e-d330-4a93-a649-45fd9b7187ab","year":2018},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:e8c798587c3382b061b54117f76564de822d785459855b5880610d2ecce73511","observation_id":"80d547e1-0910-40ce-88f8-bd647c1b7107","resolution":{"observed_at":"2026-07-13T05:29:22.230322Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-07-13T11:49:36.158055+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T11:49:36.158055+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"K., & Togashi, K","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:4768abaaac9c749b4da2f12c17b0112f22434edabc7a7827a3a36722ee22b637","observation_id":"ef25b003-4a0b-4f35-9b06-d3a4193dbc3d","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6856","last_updated":"2015-04-15T19:06:41Z","snapshot_observed_at":"2026-08-16T21:36:31.797355Z","submitted_at":"2014-12-22T01:14:01Z","title":"Object Detectors Emerge in Deep Scene CNNs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6856","snapshot_observed_at":"2026-07-13T05:25:47.083510Z","title":"2014, in International Conference on Learning Representations, doi: 10.48550/arXiv.1412.6856","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-13T05:25:47.083510Z"},"links":{"cited_paper":"/paper/1412.6856","citing_paper":"/paper/2607.08969"},"observation_digest":"sha256:922dccaf4f977969232d4b5a9adaa595fb5b19d9b67471db05b7bcafb6f06b61","observation_id":"86f18d00-6893-47f6-8a02-6093a55cfe70","resolution":{"observed_at":"2026-07-13T05:25:47.083510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.08969","last_updated":"2026-07-09T22:12:26Z","latest_version":1,"primary_category":"astro-ph.SR","snapshot_observed_at":"2026-08-16T21:38:09.975793Z","submitted_at":"2026-07-09T22:12:26Z","title":"Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations"},"reference_resolution":{"displayed":40,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":24,"verified_exact":16,"verified_fuzzy":0},"total_outbound_references":40},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2607.08969."}