{"as_of":"2026-08-13T12:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2a34c36831f8e7160779bfc72c2e1597ff73c80d83fede3195801eb59765f8e2","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T14:31:03.665226Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+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/2411.15140/citation-record","integrity":"/paper/2411.15140/integrity","json":"/paper/2411.15140/citation-record.json","paper":"/paper/2411.15140"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1807.06209","last_updated":"2021-08-09T10:43:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2018-07-17T04:05:07Z","title":"Planck 2018 results. VI. Cosmological parameters","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.06209","snapshot_observed_at":"2026-08-12T14:31:03.518457Z","title":"Aghanim, Y","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.518457Z"},"links":{"cited_paper":"/paper/1807.06209","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:a4cfc87574d8f72871b9da37702dfe2c1c5a3cfa39a7b6cf1e9bbf3f192e4a90","observation_id":"9851dff5-70b4-4d13-a3fa-bc0e854655dd","resolution":{"observed_at":"2026-08-12T14:31:03.518457Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.162690Z","title":"Thornton, P.A.R","venue":null,"work_id":"bd6e323f-12c4-4016-b934-cf850dc83a26","year":2016},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.521672Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:6d798dbd8d2e60c48569c352ab62c15cd080eb573dcee033042375395dc6967d","observation_id":"e55bd3ce-c003-4f13-bac9-9759e12c5846","resolution":{"observed_at":"2026-08-12T14:31:04.166140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1407.2973","last_updated":"2014-07-10T21:32:57Z","snapshot_observed_at":"2026-07-06T03:48:44.391683Z","submitted_at":"2014-07-10T21:32:57Z","title":"SPT-3G: A Next-Generation Cosmic Microwave Background Polarization Experiment on the South Pole Telescope","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1407.2973","snapshot_observed_at":"2026-08-12T14:31:03.524294Z","title":"Benson, P.A.R","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.524294Z"},"links":{"cited_paper":"/paper/1407.2973","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:b89cc29b8594ca2cf1062806449a8d53c18a16cb94cb066da304a2cd99c1e104","observation_id":"6b9f4f49-3080-4d80-806d-e63bd2d979d5","resolution":{"observed_at":"2026-08-12T14:31:03.524294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1408.4788","last_updated":"2014-08-20T19:59:40Z","snapshot_observed_at":"2026-07-06T03:52:13.033597Z","submitted_at":"2014-08-20T19:59:40Z","title":"CLASS: The Cosmology Large Angular Scale Surveyor","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1408.4788","snapshot_observed_at":"2026-08-12T14:31:03.527451Z","title":"Essinger-Hileman, A","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.527451Z"},"links":{"cited_paper":"/paper/1408.4788","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:7a8e156bd7841dab44809e4584cc03b56a62df5ff04405bd4162992abbf22830","observation_id":"9fa5d081-925e-4bc7-9bb2-f27a102bb33a","resolution":{"observed_at":"2026-08-12T14:31:03.527451Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1808.07445","last_updated":"2019-03-01T10:51:03Z","snapshot_observed_at":"2026-07-06T06:56:54.438585Z","submitted_at":"2018-08-22T17:19:17Z","title":"The Simons Observatory: Science goals and forecasts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.07445","snapshot_observed_at":"2026-08-12T14:31:03.530370Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.530370Z"},"links":{"cited_paper":"/paper/1808.07445","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:2500e1de98b1cf271d9f9a45e6573e27def501264a1c08ce5fce87aa51f5cc9a","observation_id":"6c51bc39-162f-4d63-b537-9958932298d5","resolution":{"observed_at":"2026-08-12T14:31:03.530370Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1907.04473","last_updated":"2019-07-10T01:01:01Z","snapshot_observed_at":"2026-08-10T23:33:51.688803Z","submitted_at":"2019-07-10T01:01:01Z","title":"CMB-S4 Science Case, Reference Design, and Project Plan","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.04473","snapshot_observed_at":"2026-08-12T14:31:03.533303Z","title":"Abazajian, G","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.533303Z"},"links":{"cited_paper":"/paper/1907.04473","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:7c793cae38ed2401c8181628697209b99cce794a2ae91d5fcc7c02da6d756914","observation_id":"87b532f9-5266-429d-838f-ea333f1f4d76","resolution":{"observed_at":"2026-08-12T14:31:03.533303Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.153847Z","title":"Zeldovich, V.G","venue":null,"work_id":"a3ebe07f-e9c0-4ddc-9267-924c1fa68197","year":1968},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.536464Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:aa2a68b0fe06a801ac21d60b49f90672e29034c3fc627cc29477db6f3594a93f","observation_id":"8f5f3d2d-dff0-4e4d-8b25-f56f3731f8a1","resolution":{"observed_at":"2026-08-12T14:31:04.156950Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.145912Z","title":"Peebles, Recombination of the Primeval Plasma , ApJ 153 (1968) 1","venue":null,"work_id":"d8b561f8-ec00-4f40-b632-1bce150d462a","year":1968},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.538978Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:9b285dc85f2760816b4eee8e78734bf2f503a2f8b00ee4725530c3171bc903bd","observation_id":"27e0222b-07ce-4e4a-ad9a-f4d2ad946657","resolution":{"observed_at":"2026-08-12T14:31:04.148627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.138663Z","title":"Seager, D.D","venue":null,"work_id":"313e4418-d2c3-4da3-8a80-fb1a37d6b8d7","year":1999},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.541381Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:96db3a85dcbc4ab29f7d3052ec0016e4e90c713b4b595bbf765c44413acd6a91","observation_id":"4c756ec1-0b84-4ab2-9de9-16e3f81a62bc","resolution":{"observed_at":"2026-08-12T14:31:04.141227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.131196Z","title":"Ali-Ha ¨ ımoud and C.M","venue":null,"work_id":"e88f067b-64d5-4c0a-8c80-1b6046380b57","year":2011},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.543890Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:24ec63feb937d8d397793f5923d1c05626f7c3b16b3daa05f6651561c88ac1ad","observation_id":"3fecff25-ef2f-4de4-8d18-00f3846ab516","resolution":{"observed_at":"2026-08-12T14:31:04.133719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.123303Z","title":"Lee and Y","venue":null,"work_id":"c29f1606-6e3c-4b97-bac7-f78347b3744a","year":2020},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.546153Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:99517725213f35cdb284416973b256e6e9b7233aac99cb96d60660aa7f98ba52","observation_id":"1e3a4d52-5cd4-4067-a72c-7479c8ed3511","resolution":{"observed_at":"2026-08-12T14:31:04.125895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.04385","last_updated":"2021-11-02T12:06:44Z","snapshot_observed_at":"2026-08-13T06:05:51.033940Z","submitted_at":"2020-01-13T16:40:35Z","title":"Universal Differential Equations for Scientific Machine Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.04385","snapshot_observed_at":"2026-08-12T14:31:03.548827Z","title":"Rackauckas, Y","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.548827Z"},"links":{"cited_paper":"/paper/2001.04385","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:526874c3129b591a673028877562214efe57a3b7e2b938744bb3e9a1a5bb2380","observation_id":"8b90ddba-79b0-4b23-a274-79677d801f0e","resolution":{"observed_at":"2026-08-12T14:31:03.548827Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.115829Z","title":"Bolibar, F","venue":null,"work_id":"4cf96286-570a-4498-a31c-7206ecfd1f30","year":2023},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.551525Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:4007b39ad04ed4f66e98052e29349b57f915f340f039fff8d5e421015b4885fa","observation_id":"7c32a365-4bb3-4eca-92c4-c0e7a87b18f0","resolution":{"observed_at":"2026-08-12T14:31:04.118508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.108091Z","title":"Lima, C.M","venue":null,"work_id":"6decac09-1344-444a-9294-95ec5f609313","year":2023},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.553487Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:cc8c6e4caf2bfa5efb6cdb11f5b1e6b220e1397f73c825e4b34e838ffc45d7fd","observation_id":"86feaf92-a8b1-41b7-ba85-3609bf3f000e","resolution":{"observed_at":"2026-08-12T14:31:04.110926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.097941Z","title":"Vortmeyer-Kley, P","venue":null,"work_id":"86664eae-eaae-4942-9298-cd4197369ad6","year":2021},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.555427Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:80d2b4062705a01a63f038bcaeb6d100b761fc062b22055b5d5a9703fee245c0","observation_id":"aa8a1691-45e7-40d3-99c7-5a9249e5713e","resolution":{"observed_at":"2026-08-12T14:31:04.100775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"0902.0429","last_updated":"2010-08-24T20:31:19Z","snapshot_observed_at":"2026-07-06T01:53:52.860357Z","submitted_at":"2009-02-03T04:43:47Z","title":"The Coyote Universe II: Cosmological Models and Precision Emulation of the Nonlinear Matter Power Spectrum","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"0902.0429","snapshot_observed_at":"2026-08-12T14:31:03.557620Z","title":"Heitmann, D","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.557620Z"},"links":{"cited_paper":"/paper/0902.0429","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:95fc9dd99f3fab1f64ff86877a62ae783732979cfb56b1cc9a90dbb0a68f8021","observation_id":"0913147d-b9ad-44a7-bd85-4aa481a6e9d7","resolution":{"observed_at":"2026-08-12T14:31:03.557620Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"astro-ph/0703445","last_updated":"2007-03-16T16:19:03Z","snapshot_observed_at":"2026-07-07T01:08:10.508068Z","submitted_at":"2007-03-16T16:19:03Z","title":"{\\sc CosmoNet}: fast cosmological parameter estimation in non-flat models using neural networks","version":1},"cited_work":{"arxiv_id":"astro-ph/0703445","doi":null,"metadata_source":"pith","pith_arxiv_id":"astro-ph/0703445","snapshot_observed_at":"2026-08-12T14:31:04.017392Z","title":"{\\sc CosmoNet}: fast cosmological parameter estimation in non-flat models using neural networks","venue":"astro-ph","work_id":"590af029-a4fa-43d3-ae82-09b5c3a0e808","year":2007},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.559761Z"},"links":{"cited_paper":"/paper/astro-ph/0703445","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:acee4fa02a74537a164bba80be661d7270e91bb2e53bb69d0ef78aae2a85cc79","observation_id":"88e2fe03-d14b-4b89-9b8b-1c1340107772","resolution":{"observed_at":"2026-08-12T14:31:04.020695Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.06551","last_updated":"2020-07-15T10:09:25Z","snapshot_observed_at":"2026-08-07T12:38:43.384139Z","submitted_at":"2020-05-13T19:41:49Z","title":"Parameter Inference for Weak Lensing using Gaussian Processes and MOPED","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.06551","snapshot_observed_at":"2026-08-12T14:31:03.562180Z","title":"Mootoovaloo, A.F","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.562180Z"},"links":{"cited_paper":"/paper/2005.06551","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:47c36414fcd7823df1021f72179428099c071af9df3769187eba37219e862b05","observation_id":"bc9a68ef-ec24-4399-9caa-88955f022f4a","resolution":{"observed_at":"2026-08-12T14:31:03.562180Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.03846","last_updated":"2022-01-31T10:28:30Z","snapshot_observed_at":"2026-08-10T18:43:45.777068Z","submitted_at":"2021-06-07T17:58:33Z","title":"COSMOPOWER: emulating cosmological power spectra for accelerated Bayesian inference from next-generation surveys","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.03846","snapshot_observed_at":"2026-08-12T14:31:03.564445Z","title":"Spurio Mancini, D","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.564445Z"},"links":{"cited_paper":"/paper/2106.03846","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:326c1da1fc0f813722002bc24caaa271905d99569ac1c8af357ab5989e8ba69f","observation_id":"2e982048-fd4f-4552-bcda-da33711bcc9d","resolution":{"observed_at":"2026-08-12T14:31:03.564445Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"astro-ph/0606709","last_updated":"2006-06-29T04:33:35Z","snapshot_observed_at":"2026-07-07T01:01:23.096289Z","submitted_at":"2006-06-29T04:33:35Z","title":"Pico: Parameters for the Impatient Cosmologist","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"astro-ph/0606709","snapshot_observed_at":"2026-08-12T14:31:03.567151Z","title":"Fendt and B.D","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.567151Z"},"links":{"cited_paper":"/paper/astro-ph/0606709","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:fb115e1a4da93c4824bbbca01e4ec2918b840489b52fb520b5796eb0a8a3e955","observation_id":"c05c8184-c520-4349-a621-1ffa7731c08e","resolution":{"observed_at":"2026-08-12T14:31:03.567151Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11288","last_updated":"2020-10-21T19:59:58Z","snapshot_observed_at":"2026-08-10T20:59:23.966413Z","submitted_at":"2020-10-21T19:59:58Z","title":"Euclid preparation: IX. EuclidEmulator2 -- Power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11288","snapshot_observed_at":"2026-08-12T14:31:03.569882Z","title":"Knabenhans, J","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.569882Z"},"links":{"cited_paper":"/paper/2010.11288","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:c995fdcd4d27eae6866dded2d4c9bfee0f63c3bf9f52c6ef0d523fd3550040bd","observation_id":"c572b197-36fd-4b0d-ba96-e269c6415344","resolution":{"observed_at":"2026-08-12T14:31:03.569882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14568","last_updated":"2022-06-17T10:24:11Z","snapshot_observed_at":"2026-08-09T15:25:41.052001Z","submitted_at":"2021-04-29T18:00:01Z","title":"Accelerating Large-Scale-Structure data analyses by emulating Boltzmann solvers and Lagrangian Perturbation Theory","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.14568","snapshot_observed_at":"2026-08-12T14:31:03.572629Z","title":"Aric` o, R.E","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.572629Z"},"links":{"cited_paper":"/paper/2104.14568","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:5e9e65491a6664b3d5e39f74de7236f26f64e2e8151d13c2f6bf85bec6d038d6","observation_id":"760291cc-3642-4ecf-bb4b-1fe92dce2aab","resolution":{"observed_at":"2026-08-12T14:31:03.572629Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.06245","last_updated":"2021-07-06T09:32:41Z","snapshot_observed_at":"2026-07-06T09:12:07.167333Z","submitted_at":"2020-04-14T00:31:09Z","title":"The BACCO Simulation Project: Exploiting the full power of large-scale structure for cosmology","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.06245","snapshot_observed_at":"2026-08-12T14:31:03.575165Z","title":"Angulo, M","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.575165Z"},"links":{"cited_paper":"/paper/2004.06245","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:12f6b9d3b4b23b0b67a6dc07eaa2e96d6aa408dd069a2a1c4afdedbc29314d0b","observation_id":"a90b01b4-5386-4c57-b9e9-d8cffa7bbcbf","resolution":{"observed_at":"2026-08-12T14:31:03.575165Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1907.05764","last_updated":"2019-07-15T15:22:47Z","snapshot_observed_at":"2026-08-09T14:33:25.203786Z","submitted_at":"2019-07-12T14:24:06Z","title":"CosmicNet I: Physics-driven implementation of neural networks within Boltzmann-Einstein solvers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.05764","snapshot_observed_at":"2026-08-12T14:31:03.578825Z","title":"Albers, C","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.578825Z"},"links":{"cited_paper":"/paper/1907.05764","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:77bd9444d91bba5ab7d40289796737f2688113e6504a52d457c0d591e9b59e6d","observation_id":"b666a72f-0dba-489e-94e2-54aff64dd86f","resolution":{"observed_at":"2026-08-12T14:31:03.578825Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.04594","last_updated":"2022-06-14T11:17:28Z","snapshot_observed_at":"2026-07-06T13:19:08.374655Z","submitted_at":"2022-06-09T16:21:57Z","title":"Field Level Neural Network Emulator for Cosmological N-body Simulations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.04594","snapshot_observed_at":"2026-08-12T14:31:03.581301Z","title":"Jamieson, Y","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.581301Z"},"links":{"cited_paper":"/paper/2206.04594","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:b44c703f3a9c4379c81e7e50b70efcf020750461f01fa0f934201e3269cdd05d","observation_id":"8a7e0d5f-05f5-49e2-87c0-0c8a2a42e110","resolution":{"observed_at":"2026-08-12T14:31:03.581301Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.14208","last_updated":"2022-06-28T18:00:01Z","snapshot_observed_at":"2026-08-09T01:13:58.637614Z","submitted_at":"2022-06-28T18:00:01Z","title":"Fast emulation of two-point angular statistics for photometric galaxy surveys","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.14208","snapshot_observed_at":"2026-08-12T14:31:03.583864Z","title":"Bonici, L","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.583864Z"},"links":{"cited_paper":"/paper/2206.14208","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:c1538030639b5c1bdabee6054f3d4612daf8905d28b5f4d9c072d255a7f35a1e","observation_id":"1f3428c0-f9e2-48a1-9312-19fb94fdcf66","resolution":{"observed_at":"2026-08-12T14:31:03.583864Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.14339","last_updated":"2024-01-29T13:44:53Z","snapshot_observed_at":"2026-08-13T10:47:22.828234Z","submitted_at":"2023-07-26T17:58:09Z","title":"Capse.jl: efficient and auto-differentiable CMB power spectra emulation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.14339","snapshot_observed_at":"2026-08-12T14:31:03.586595Z","title":"Bonici, F","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.586595Z"},"links":{"cited_paper":"/paper/2307.14339","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:ba8ac22f1acd3c679982b02af25caef94d3182a299141d3450d175d82623fa81","observation_id":"ae3a1d2f-deed-4aa5-b38e-47df29f95e59","resolution":{"observed_at":"2026-08-12T14:31:03.586595Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12379","last_updated":"2023-06-06T18:14:12Z","snapshot_observed_at":"2026-08-13T12:38:24.429902Z","submitted_at":"2023-02-24T00:50:52Z","title":"Galaxy Clustering in the Mira-Titan Universe I: Emulators for the redshift space galaxy correlation function and galaxy-galaxy lensing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12379","snapshot_observed_at":"2026-08-12T14:31:03.589285Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.589285Z"},"links":{"cited_paper":"/paper/2302.12379","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:d88fb2edcf9b3f57d58bf6908f161ce8fe2773050e626cd152fc677d51b6c0e7","observation_id":"cecf4e26-fe0d-4e6e-b6a7-162a49272d57","resolution":{"observed_at":"2026-08-12T14:31:03.589285Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.01591","last_updated":"2023-03-02T21:28:21Z","snapshot_observed_at":"2026-08-13T12:33:08.396673Z","submitted_at":"2023-03-02T21:28:21Z","title":"High-accuracy emulators for observables in $\\Lambda$CDM, $N_\\mathrm{eff}$, $\\Sigma m_\\nu$, and $w$ cosmologies","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.01591","snapshot_observed_at":"2026-08-12T14:31:03.591730Z","title":"Bolliet, A","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.591730Z"},"links":{"cited_paper":"/paper/2303.01591","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:0e6bce715e0c10c72c904d550e855beb4aa2fc954c5c01f8cf2b8e54ff728cdf","observation_id":"f9d8eaad-247a-4a50-8180-f05dfeaa8302","resolution":{"observed_at":"2026-08-12T14:31:03.591730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.12345","last_updated":"2022-07-25T17:01:04Z","snapshot_observed_at":"2026-08-07T14:42:57.065376Z","submitted_at":"2022-07-25T17:01:04Z","title":"The Mira-Titan Universe IV. High Precision Power Spectrum Emulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.12345","snapshot_observed_at":"2026-08-12T14:31:03.594470Z","title":"Moran, K","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.594470Z"},"links":{"cited_paper":"/paper/2207.12345","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:1abb185373f84565808d79148c2a7eab0400c93b0527ae245675dcfed8750202","observation_id":"58ddce6e-d68c-443c-a7ce-ac0637459339","resolution":{"observed_at":"2026-08-12T14:31:03.594470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.06124","last_updated":"2022-03-11T17:48:48Z","snapshot_observed_at":"2026-07-06T12:46:54.812392Z","submitted_at":"2022-03-11T17:48:48Z","title":"Accelerating cosmological inference with Gaussian processes and neural networks -- an application to LSST Y1 weak lensing and galaxy clustering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.06124","snapshot_observed_at":"2026-08-12T14:31:03.597104Z","title":"Boruah, T","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.597104Z"},"links":{"cited_paper":"/paper/2203.06124","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:e9a75f128fe2df2a462685d68821f0d334238aa11226120131d313a31c1e21f1","observation_id":"d56a968e-b984-4d64-a0be-fbd6c9c4f05e","resolution":{"observed_at":"2026-08-12T14:31:03.597104Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.01070","last_updated":"2023-04-28T14:43:40Z","snapshot_observed_at":"2026-08-09T13:31:24.704053Z","submitted_at":"2022-08-01T18:10:52Z","title":"COMET: Clustering Observables Modelled by Emulated perturbation Theory","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.01070","snapshot_observed_at":"2026-08-12T14:31:03.599806Z","title":"Eggemeier, B","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.599806Z"},"links":{"cited_paper":"/paper/2208.01070","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:160cb1ed4ab852a0bdb3113b8a18bfeebb05eb83b1aa65a73fd7f25870c89e87","observation_id":"29101e84-c1d8-450d-a982-90a4fbf01c1e","resolution":{"observed_at":"2026-08-12T14:31:03.599806Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.05707","last_updated":"2022-07-12T17:29:22Z","snapshot_observed_at":"2026-08-13T02:18:04.626661Z","submitted_at":"2022-07-12T17:29:22Z","title":"CosmicNet II: Emulating extended cosmologies with efficient and accurate neural networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.05707","snapshot_observed_at":"2026-08-12T14:31:03.602345Z","title":"G¨ unther, J","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.602345Z"},"links":{"cited_paper":"/paper/2207.05707","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:8056c1ea067dd173bd855089b7701d5176a0777e2659468f3df69cb66e68e207","observation_id":"6c857c55-5b0d-4576-b032-f8bb3cd4117d","resolution":{"observed_at":"2026-08-12T14:31:03.602345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.02441","last_updated":"2021-11-03T18:01:41Z","snapshot_observed_at":"2026-08-13T07:31:24.560055Z","submitted_at":"2021-11-03T18:01:41Z","title":"NECOLA: Towards a Universal Field-level Cosmological Emulator","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.02441","snapshot_observed_at":"2026-08-12T14:31:03.605034Z","title":"Kaushal, F","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.605034Z"},"links":{"cited_paper":"/paper/2111.02441","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:edc906900d6d0fe0a3f11f60bc6bb764b1438e61dbebf3ce3ad2ed751faca0dd","observation_id":"c3e3a4f4-c84e-46fc-8c1d-993347972ab7","resolution":{"observed_at":"2026-08-12T14:31:03.605034Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.15236","last_updated":"2022-01-25T18:47:42Z","snapshot_observed_at":"2026-08-11T14:31:38.793572Z","submitted_at":"2021-09-30T16:16:11Z","title":"$\\texttt{matryoshka}$: Halo Model Emulator for the Galaxy Power Spectrum","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.15236","snapshot_observed_at":"2026-08-12T14:31:03.607262Z","title":"Donald-McCann, F","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.607262Z"},"links":{"cited_paper":"/paper/2109.15236","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:236681d2dac975525b3e6edf80807310abc5c0e96fb753677e953e9d7f5df51b","observation_id":"0f797902-c521-4123-8780-b7f7df772b6c","resolution":{"observed_at":"2026-08-12T14:31:03.607262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.02256","last_updated":"2021-11-08T11:54:52Z","snapshot_observed_at":"2026-08-13T02:16:25.909354Z","submitted_at":"2021-05-05T18:01:39Z","title":"Kernel-Based Emulator for the 3D Matter Power Spectrum from CLASS","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.02256","snapshot_observed_at":"2026-08-12T14:31:03.609725Z","title":"Mootoovaloo, A.H","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.609725Z"},"links":{"cited_paper":"/paper/2105.02256","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:f15f8b2201a21d29c2b6db88e523fa4cf4eb122d195b3a90aea940f44b7dbbf3","observation_id":"84180ed3-8505-4164-95c3-269eb1051ee1","resolution":{"observed_at":"2026-08-12T14:31:03.609725Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.01081","last_updated":"2021-10-27T21:05:51Z","snapshot_observed_at":"2026-08-11T03:47:15.279063Z","submitted_at":"2021-05-03T18:00:03Z","title":"Multi-Fidelity Emulation for the Matter Power Spectrum using Gaussian Processes","version":2},"cited_work":{"arxiv_id":"2105.01081","doi":null,"metadata_source":"pith","pith_arxiv_id":"2105.01081","snapshot_observed_at":"2026-08-12T14:31:03.897611Z","title":"Multi-Fidelity Emulation for the Matter Power Spectrum using Gaussian Processes","venue":"astro-ph.CO","work_id":"43ca594c-938d-46ec-a6fd-703a1ac403d4","year":2021},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.611994Z"},"links":{"cited_paper":"/paper/2105.01081","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:2b06d4cc2e64fb7f16538c3b413a317143863ff933e09fe541b6144792f52feb","observation_id":"cefaa138-6ec7-46c2-b971-224d3d7210d6","resolution":{"observed_at":"2026-08-12T14:31:03.900639Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.11014","last_updated":"2021-07-22T17:21:55Z","snapshot_observed_at":"2026-08-08T17:38:56.218505Z","submitted_at":"2021-01-26T19:00:02Z","title":"The cosmology dependence of galaxy clustering and lensing from a hybrid $N$-body-perturbation theory model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.11014","snapshot_observed_at":"2026-08-12T14:31:03.614676Z","title":"Kokron, J","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.614676Z"},"links":{"cited_paper":"/paper/2101.11014","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:6c7aa177f81282be7aedd17d3f9d4ed217a4e82872e01748ed9444625ababbfd","observation_id":"d9d465ac-1241-4827-9f4c-d265f92ee067","resolution":{"observed_at":"2026-08-12T14:31:03.614676Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.01858","last_updated":"2021-01-08T11:17:50Z","snapshot_observed_at":"2026-08-11T00:40:28.523055Z","submitted_at":"2020-09-03T18:00:09Z","title":"HMcode-2020: Improved modelling of non-linear cosmological power spectra with baryonic feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.01858","snapshot_observed_at":"2026-08-12T14:31:03.618051Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.618051Z"},"links":{"cited_paper":"/paper/2009.01858","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:fb6e867c9ad5a3cb131e3a9dde077f9fd52f1c37f7e29927f0e70289dba3d618","observation_id":"408ac96a-79fc-472b-ac0c-b2e40cfa9841","resolution":{"observed_at":"2026-08-12T14:31:03.618051Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.06122","last_updated":"2020-10-19T02:08:34Z","snapshot_observed_at":"2026-08-10T23:08:10.153048Z","submitted_at":"2020-05-13T02:35:19Z","title":"Accurate emulator for the redshift-space power spectrum of dark matter halos and its application to galaxy power spectrum","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.06122","snapshot_observed_at":"2026-08-12T14:31:03.620829Z","title":"Kobayashi, T","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.620829Z"},"links":{"cited_paper":"/paper/2005.06122","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:5edecdc05bc0927b42f0495d454bf40e30654e917d6e938a2c431990a294e64a","observation_id":"39d8d1fa-e496-412d-9f3f-f9277941bd3b","resolution":{"observed_at":"2026-08-12T14:31:03.620829Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1907.06293","last_updated":"2019-12-04T00:56:46Z","snapshot_observed_at":"2026-08-03T20:18:58.379700Z","submitted_at":"2019-07-14T22:43:46Z","title":"Cosmology with galaxy-galaxy lensing on non-perturbative scales: Emulation method and application to BOSS LOWZ","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.06293","snapshot_observed_at":"2026-08-12T14:31:03.623444Z","title":"Wibking, D.H","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.623444Z"},"links":{"cited_paper":"/paper/1907.06293","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:eba6cb08bd1842e4ef91bc6c30c3c703eb364dd0e88ddc7ebca3f9fa9df2397b","observation_id":"54f7c8a8-a01e-4c06-8c3b-94ae5ccac6a4","resolution":{"observed_at":"2026-08-12T14:31:03.623444Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.09504","last_updated":"2019-07-26T13:32:16Z","snapshot_observed_at":"2026-08-10T08:47:49.871939Z","submitted_at":"2018-11-23T14:59:14Z","title":"Dark Quest. I. Fast and Accurate Emulation of Halo Clustering Statistics and Its Application to Galaxy Clustering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.09504","snapshot_observed_at":"2026-08-12T14:31:03.625999Z","title":"Nishimichi, M","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.625999Z"},"links":{"cited_paper":"/paper/1811.09504","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:c3c10c24fdda4b1487317852e7c18d1943c06e7e905938985b564471c981f8d8","observation_id":"4ed77ceb-25ba-4cf9-a8a0-a52c748a2992","resolution":{"observed_at":"2026-08-12T14:31:03.625999Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.05867","last_updated":"2018-04-24T01:07:02Z","snapshot_observed_at":"2026-08-05T07:15:48.224358Z","submitted_at":"2018-04-16T18:05:14Z","title":"The Aemulus Project III: Emulation of the Galaxy Correlation Function","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.05867","snapshot_observed_at":"2026-08-12T14:31:03.628750Z","title":"Zhai, J.L","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.628750Z"},"links":{"cited_paper":"/paper/1804.05867","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:c85736f502692020a3b9d6b6b2ffc8f0b362c48ffe4cd861e52b9e68fef0d9f6","observation_id":"7a5668d6-34cf-4aba-a3b5-f3b809bfeaa0","resolution":{"observed_at":"2026-08-12T14:31:03.628750Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.04654","last_updated":"2023-01-23T20:37:03Z","snapshot_observed_at":"2026-08-12T10:55:07.102544Z","submitted_at":"2018-12-11T19:15:35Z","title":"An Emulator for the Lyman-alpha Forest","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.04654","snapshot_observed_at":"2026-08-12T14:31:03.631480Z","title":"Bird, K.K","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.631480Z"},"links":{"cited_paper":"/paper/1812.04654","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:c2d965478c5a321d9e651e0b17f713c76e828916fb56c170d40078b38422791b","observation_id":"6130cf9f-b2bb-4081-94d3-980d6e4da24b","resolution":{"observed_at":"2026-08-12T14:31:03.631480Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1708.00011","last_updated":"2018-01-02T10:41:52Z","snapshot_observed_at":"2026-07-06T05:53:28.633302Z","submitted_at":"2017-07-31T18:00:08Z","title":"Emulation of reionization simulations for Bayesian inference of astrophysics parameters using neural networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.00011","snapshot_observed_at":"2026-08-12T14:31:03.634276Z","title":"Schmit and J.R","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.634276Z"},"links":{"cited_paper":"/paper/1708.00011","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:603fc523fe66d8d0c1e4d15e1663d1fadbdc5b8269e3d31ffdd8ed32e44d76d8","observation_id":"e93c87dd-ebe0-4773-9e19-7f93a61dbb16","resolution":{"observed_at":"2026-08-12T14:31:03.634276Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.03388","last_updated":"2017-05-09T15:35:22Z","snapshot_observed_at":"2026-07-06T05:41:57.566336Z","submitted_at":"2017-05-09T15:35:22Z","title":"The Mira-Titan Universe II: Matter Power Spectrum Emulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.03388","snapshot_observed_at":"2026-08-12T14:31:03.636969Z","title":"Lawrence, K","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.636969Z"},"links":{"cited_paper":"/paper/1705.03388","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:69e3b171f674483dfae38984784a3f9d61b3c94e657e92c2aea407a81a8fdfdd","observation_id":"180df48f-e7ce-430e-a9a5-e01d9622409f","resolution":{"observed_at":"2026-08-12T14:31:03.636969Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1311.6444","last_updated":"2015-08-16T22:34:45Z","snapshot_observed_at":"2026-07-06T03:29:11.747937Z","submitted_at":"2013-11-25T20:35:33Z","title":"Cosmic Emulation: Fast Predictions for the Galaxy Power Spectrum","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1311.6444","snapshot_observed_at":"2026-08-12T14:31:03.639570Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.639570Z"},"links":{"cited_paper":"/paper/1311.6444","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:792304dae2be852c674cbf733b16108d4d11c6b42ae4c92ac837f5cf85160e64","observation_id":"efe5da96-6679-4071-b267-32d69e687b3b","resolution":{"observed_at":"2026-08-12T14:31:03.639570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.2101","last_updated":"2013-12-10T21:04:37Z","snapshot_observed_at":"2026-08-10T11:58:22.568037Z","submitted_at":"2013-12-07T15:10:54Z","title":"PkANN - II. A non-linear matter power spectrum interpolator developed using artificial neural networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.2101","snapshot_observed_at":"2026-08-12T14:31:03.642550Z","title":"Agarwal, F.B","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.642550Z"},"links":{"cited_paper":"/paper/1312.2101","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:1de8c3cb3ac9e0a4a5ee913a8537263646a3f690efe71041e0062020cfa4ca0f","observation_id":"9f91cb4a-60d2-4e36-9a3a-ce5a7e664342","resolution":{"observed_at":"2026-08-12T14:31:03.642550Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1304.7849","last_updated":"2013-11-25T20:24:22Z","snapshot_observed_at":"2026-07-06T03:12:17.296079Z","submitted_at":"2013-04-30T03:35:13Z","title":"The Coyote Universe Extended: Precision Emulation of the Matter Power Spectrum","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1304.7849","snapshot_observed_at":"2026-08-12T14:31:03.645172Z","title":"Heitmann, E","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.645172Z"},"links":{"cited_paper":"/paper/1304.7849","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:c1825bfe7f621fb0b6b17e4d7f513e43a21535b3a37905bc604c26142c03ebd6","observation_id":"e8fa0be3-f529-4a99-84c1-a9f4f4aad6a8","resolution":{"observed_at":"2026-08-12T14:31:03.645172Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"0912.4490","last_updated":"2013-05-10T13:51:48Z","snapshot_observed_at":"2026-07-06T02:04:37.396414Z","submitted_at":"2009-12-22T19:09:48Z","title":"The Coyote Universe III: Simulation Suite and Precision Emulator for the Nonlinear Matter Power Spectrum","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"0912.4490","snapshot_observed_at":"2026-08-12T14:31:03.647864Z","title":"Lawrence, K","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.647864Z"},"links":{"cited_paper":"/paper/0912.4490","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:73873bb454040f40911dbdcecd70bd0dd59ad1483494d0bf47e1020188fa339a","observation_id":"e363e3d4-29e0-4ff4-9655-371f6285ecb5","resolution":{"observed_at":"2026-08-12T14:31:03.647864Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.10656","last_updated":"2020-07-09T16:53:58Z","snapshot_observed_at":"2026-08-12T08:50:15.964327Z","submitted_at":"2020-05-21T14:02:30Z","title":"H0 tension or T0 tension?","version":2},"cited_work":{"arxiv_id":"2005.10656","doi":null,"metadata_source":"pith","pith_arxiv_id":"2005.10656","snapshot_observed_at":"2026-08-12T14:31:03.812388Z","title":"H0 tension or T0 tension?","venue":"astro-ph.CO","work_id":"0500a13e-d133-4045-8480-249e7b036fab","year":2020},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.650658Z"},"links":{"cited_paper":"/paper/2005.10656","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:1c933ae575760862b5dfeec9d299af88c4afcad41e3cc900a1ce2a3d9177e47a","observation_id":"1fe14749-1da1-41cc-b33d-a6927aa8e657","resolution":{"observed_at":"2026-08-12T14:31:03.815338Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.088677Z","title":"Tsitouras, Runge–kutta pairs of order 5(4) satisfying only the first column simplifying assumption, Computers & Mathematics with Applications 62 (2011) 770","venue":null,"work_id":"a50ffa42-aad6-49a7-bdfa-e9b40d079b51","year":2011},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.653207Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:76753e9fa406906a36207efbb77f1b0336259419baba3196a0c58487fd19ee5f","observation_id":"6eeb1a84-af53-4d48-b8af-8aefe0055804","resolution":{"observed_at":"2026-08-12T14:31:04.092094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T14:31:03.655322Z","title":"Kingma and J","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.655322Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:6522423c603757662f85d99954b9684082e55de8766bd8db0adbe4ddb0c6e9a1","observation_id":"8a7c9ede-ea7a-4e40-8a54-ee6623fa7c61","resolution":{"observed_at":"2026-08-12T14:31:03.655322Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1902.02376","last_updated":"2019-02-06T19:42:14Z","snapshot_observed_at":"2026-08-10T07:57:06.124456Z","submitted_at":"2019-02-06T19:42:14Z","title":"DiffEqFlux.jl - A Julia Library for Neural Differential Equations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.02376","snapshot_observed_at":"2026-08-12T14:31:03.657360Z","title":"Rackauckas, M","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.657360Z"},"links":{"cited_paper":"/paper/1902.02376","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:1de232019a01a205cb917143328b10c5805d287cc26162d53469d160216dd3ef","observation_id":"734dccf3-c7b3-41d8-929e-caa10f772fe7","resolution":{"observed_at":"2026-08-12T14:31:03.657360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.06786","last_updated":"2021-12-17T10:42:30Z","snapshot_observed_at":"2026-07-06T11:47:40.777131Z","submitted_at":"2021-09-14T15:56:37Z","title":"Multiple shooting for training neural differential equations on time series","version":2},"cited_work":{"arxiv_id":"2109.06786","doi":null,"metadata_source":"pith","pith_arxiv_id":"2109.06786","snapshot_observed_at":"2026-08-12T14:31:03.794499Z","title":"Multiple shooting for training neural differential equations on time series","venue":"cs.LG","work_id":"4a3c2095-3190-40ac-980a-65763a17ee35","year":2021},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.660615Z"},"links":{"cited_paper":"/paper/2109.06786","citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:c0cd793836bbd790e2c39b047b8ec3e68adb1ef634c8661d901e125aaebe2423","observation_id":"668e6482-eefe-47c7-b590-ea9ec63eeb35","resolution":{"observed_at":"2026-08-12T14:31:03.799093Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:31:04.074776Z","title":"Seager, D.D","venue":null,"work_id":"63110755-2eaf-452f-8610-4887d5e57a17","year":2000},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.662851Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:be2add96b6b4cb85df9d22479ada52f3c65f07c1f6b3fda5167a4dde6fd2ea81","observation_id":"4c1a8125-5aca-442e-b31b-496f7bc52978","resolution":{"observed_at":"2026-08-12T14:31:04.078304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T14:31:03.665226Z","title":"Hazumi, P.A.R","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-12T14:31:03.665226Z"},"links":{"citing_paper":"/paper/2411.15140"},"observation_digest":"sha256:52b7f3284d4265d6bbe330b0c8f46a5051278b57b48e0d7df89d30a0b30bd2cf","observation_id":"1ac98368-8239-4dfb-acfe-f9c4adc47f70","resolution":{"observed_at":"2026-08-12T14:31:03.665226Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.15140","last_updated":"2024-11-26T20:13:59Z","latest_version":2,"primary_category":"astro-ph.CO","snapshot_observed_at":"2026-08-12T14:25:03.757691Z","submitted_at":"2024-11-22T18:59:52Z","title":"Emulating Recombination with Neural Networks using Universal Differential Equations"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":42,"verified_exact":4,"verified_fuzzy":11},"total_outbound_references":57},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2411.15140."}