{"as_of":"2026-08-17T17:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a04bb1f05ee59e1570b28bda7f9ff91a5cac4d343b4bd70d9d64bf26e9a7551e","coverage":[{"denominator":111,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T23:30:36.424920Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2505.04681/citation-record","integrity":"/paper/2505.04681/integrity","json":"/paper/2505.04681/citation-record.json","paper":"/paper/2505.04681"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:30:36.018884Z","title":", \" * write output.state after.block = add.period write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.018884Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:d5d3e6e9e64b1fee76f312b8a10f24b52df478217f03991dd39243dcd2fcfde1","observation_id":"98b8531a-939a-4a88-8b8f-5e6ef37e2984","resolution":{"observed_at":"2026-08-15T23:30:36.018884Z","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":"2026-08-15T23:30:36.024062Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.024062Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:6ae737bb4d964685f76ff75c5530772e92e26e99410b8a1391ba0eebfdc962f5","observation_id":"07a05b7e-b3bf-41c4-9a2e-ebe34bad9627","resolution":{"observed_at":"2026-08-15T23:30:36.024062Z","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":"2026-08-15T23:30:36.029456Z","title":"w'w8 j- /|bI<԰+ X + lp y pKcZe=xa+\\^ t xXw^ 狏,X/yrU˒`6 PWIpr.yqc,](r l^D Uyi;L 93NXq+NmdDI","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.029456Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:3d382fccd8d9a536256e7e5d9c5b36b4033b2c6f91675934a558168b5f065592","observation_id":"01cc8d9d-16cd-4be6-93ed-f2762efb89bd","resolution":{"observed_at":"2026-08-15T23:30:36.029456Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-15T23:30:36.055107Z","title":"N., Lisenfeld , U., et al","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.055107Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:75bbb6ce3a25196643be19f9c57befe6d9cd0bb2c769f3318e41530e52099921","observation_id":"8885e59c-745f-45ce-8858-878c3ee0352d","resolution":{"observed_at":"2026-08-15T23:30:36.055107Z","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":"2026-08-15T23:30:36.060652Z","title":null,"venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.060652Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:1eac32eb26d026110eb86bc2d752e2d2e485dc14505977df61df734bae60ab3a","observation_id":"90a7bd06-fca9-4ae4-a5c1-66d9bd415d56","resolution":{"observed_at":"2026-08-15T23:30:36.060652Z","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":"2026-08-15T23:30:36.064931Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.064931Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:9dd8cc8ac2afa2f4578f920c388a075629f032f5b60078a3e6bb84e3a1848708","observation_id":"2b730eb1-2023-43b5-b403-26bbe3cc9a3c","resolution":{"observed_at":"2026-08-15T23:30:36.064931Z","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":"2026-08-15T23:30:36.069500Z","title":null,"venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.069500Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:5bc66dc915b4831b812aaae2cfcb401ae47b305759f05e16e16c845c3f4db247","observation_id":"a1beea75-49ec-48a7-a474-1b238f14cbf3","resolution":{"observed_at":"2026-08-15T23:30:36.069500Z","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":"2026-08-15T23:30:36.073443Z","title":"2022, title From EMBER to FIRE: predicting high resolution baryon fields from dark matter simulations with deep learning , , 509, 1323, 10.1093/mnras/stab3088","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.073443Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:309da5a3df159523ee6bab64850adeccb9a35112aa8bf9175e6af8d5eb15e838","observation_id":"eccdb2a9-2ac1-4762-9b9c-ca99b6290705","resolution":{"observed_at":"2026-08-15T23:30:36.073443Z","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":"2026-08-15T23:30:36.077256Z","title":"2008, title The Star Formation Law in Nearby Galaxies on Sub-Kpc Scales , , 136, 2846, 10.1088/0004-6256/136/6/2846","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.077256Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:9f8db8d39bfd8dfdd085b5cffd55f99baca33b9a49fff6c69b6c22d3789505dd","observation_id":"b1c061c9-ade8-4fc8-bda2-529195472f68","resolution":{"observed_at":"2026-08-15T23:30:36.077256Z","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":"2026-08-15T23:30:36.081034Z","title":"D., Leroy , A","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.081034Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:ea0e76fea8bccc5359388dc2811ec9ebdb503bb9ceac4964cb7e82f87b62d69b","observation_id":"216bb681-e0fd-4ebc-915d-2a3d9c0cb61c","resolution":{"observed_at":"2026-08-15T23:30:36.081034Z","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":"2026-08-15T23:30:36.084921Z","title":"2018, title The Star Formation Rate in the Gravoturbulent Interstellar Medium , , 863, 118, 10.3847/1538-4357/aad002","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.084921Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:99b7d47243c5e3c8622bfea466856928c03fa472213b710021a85a93ad9a3f3a","observation_id":"06eaca8b-c6db-44ce-9801-2a4c6c18e74a","resolution":{"observed_at":"2026-08-15T23:30:36.084921Z","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":"2026-08-15T23:30:36.089578Z","title":"2003, title Galactic Stellar and Substellar Initial Mass Function , , 115, 763, 10.1086/376392","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.089578Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:b1f0e3b2eb06c90da59a190c78035ad906bed516019e9fe6f6f2ac091e50a598","observation_id":"9998b60e-b1cd-469b-96e3-f7faa3f8d8d3","resolution":{"observed_at":"2026-08-15T23:30:36.089578Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1603.02754","last_updated":"2016-06-10T23:23:51Z","snapshot_observed_at":"2026-08-14T22:06:53.808328Z","submitted_at":"2016-03-09T01:11:51Z","title":"XGBoost: A Scalable Tree Boosting System","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1603.02754","snapshot_observed_at":"2026-08-15T23:30:36.094015Z","title":"2016, title XGBoost: A Scalable Tree Boosting System , arXiv e-prints, arXiv:1603.02754, 10.48550/arXiv.1603.02754","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.094015Z"},"links":{"cited_paper":"/paper/1603.02754","citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:4bead4e2537a4e5532582119d1af6be14332f58065658a410443dc89d2c0261e","observation_id":"92b2ee4c-444d-41c1-9df1-b10f66323669","resolution":{"observed_at":"2026-08-15T23:30:36.094015Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.05579","last_updated":"2024-11-18T12:01:29Z","snapshot_observed_at":"2026-08-16T16:02:36.339551Z","submitted_at":"2023-01-13T14:38:24Z","title":"A survey and taxonomy of loss functions in machine learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.05579","snapshot_observed_at":"2026-08-15T23:30:36.099562Z","title":"2023, title A survey and taxonomy of loss functions in machine learning , arXiv e-prints, arXiv:2301.05579, 10.48550/arXiv.2301.05579","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.099562Z"},"links":{"cited_paper":"/paper/2301.05579","citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:e356d34eb19d5e836dfdf08c7e1258d7505bdbfc72979c2c075ee21dc956c60f","observation_id":"945089fb-2d13-4757-9f69-5c602fe8bea5","resolution":{"observed_at":"2026-08-15T23:30:36.099562Z","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":"2026-08-15T23:30:36.103964Z","title":"G., Baugh , C","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.103964Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:1c4c5ebf1466695242cef3b503d01f1761bbdfa5d4df40be6ed14155e503554e","observation_id":"c8dafab6-99cf-4024-9b1a-542d306d1645","resolution":{"observed_at":"2026-08-15T23:30:36.103964Z","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":"2026-08-15T23:30:36.108225Z","title":"E., Schinnerer , E., et al","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.108225Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:f0a7931abe8c9126ac31c360019165f106d7570f6fd56fb75b4af97e4400a6f9","observation_id":"e2c41148-cd5f-46ee-ba13-27bea14b1dbd","resolution":{"observed_at":"2026-08-15T23:30:36.108225Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"astro-ph/9706275","last_updated":"1997-06-27T05:41:54Z","snapshot_observed_at":"2026-07-07T01:17:37.392217Z","submitted_at":"1997-06-27T05:41:54Z","title":"Vertical equilibrium of molecular gas in galaxies","version":1},"cited_work":{"arxiv_id":"astro-ph/9706275","doi":"10.48550/arxiv.astro-ph/9706275","metadata_source":"pith","pith_arxiv_id":"astro-ph/9706275","snapshot_observed_at":"2026-08-16T12:16:17.039197Z","title":"Vertical equilibrium of molecular gas in galaxies","venue":"astro-ph","work_id":"c55e425f-cba5-433a-a8e5-828314c9d080","year":1997},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.112177Z"},"links":{"cited_paper":"/paper/astro-ph/9706275","citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:01e7c2a52f0dc31e6c4e0c7e198593bab40dcbc5166f0e6e7ac9ea6760e74768","observation_id":"f19e6fd0-251a-4eac-b81c-251f4326dc4b","resolution":{"observed_at":"2026-08-15T23:30:37.056627Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T23:30:36.116405Z","title":"A., Schaye , J., Bower , R","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.116405Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:397b0108a68dd145e190d1daa8e7120f8f518b16dcd705696b20d19866b471e7","observation_id":"95d1a9c7-2195-486f-aed1-dc707b0340cb","resolution":{"observed_at":"2026-08-15T23:30:36.116405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.01582","last_updated":"2023-05-05T17:44:07Z","snapshot_observed_at":"2026-08-15T03:20:28.565133Z","submitted_at":"2023-05-02T16:31:35Z","title":"Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.01582","snapshot_observed_at":"2026-08-15T23:30:36.120412Z","title":"2023, title Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl , arXiv e-prints, arXiv:2305.01582, 10.48550/arXiv.2305.01582","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.120412Z"},"links":{"cited_paper":"/paper/2305.01582","citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:944be88aa1dff5e34fa766f96e073385599114cf375bb119c5be30e9a7a95382","observation_id":"208d060e-d338-4e13-aa19-136595da706d","resolution":{"observed_at":"2026-08-15T23:30:36.120412Z","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":"2026-08-15T23:30:36.124701Z","title":"1975, title I -Divergence Geometry of Probability Distributions and Minimization Problems , The Annals of Probability, 3, 146 , 10.1214/aop/1176996454","venue":null,"work_id":null,"year":1975},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.124701Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:6c5a4d19271f244574614edb6e90ed081f18740f4a03d010f21a74c498ba9db4","observation_id":"0fb6891c-9b06-4ab1-893d-46da61ad8d22","resolution":{"observed_at":"2026-08-15T23:30:36.124701Z","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":"2026-08-15T23:30:36.128217Z","title":"2010 a , title Very High Gas Fractions and Extended Gas Reservoirs in z = 1.5 Disk Galaxies , , 713, 686, 10.1088/0004-637X/713/1/686","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.128217Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:833bd2604a477e76da4fb669a6f8fbed3570c0884bce9fca6c3ee1268b33ac68","observation_id":"ff15533d-d27e-4afb-bdb3-d915d4df663d","resolution":{"observed_at":"2026-08-15T23:30:36.128217Z","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":"2026-08-15T23:30:36.131991Z","title":"2010 b , title Different Star Formation Laws for Disks Versus Starbursts at Low and High Redshifts , , 714, L118, 10.1088/2041-8205/714/1/L118","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.131991Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:fa012e7f116221f82c6f317bde0f7f74619cc5a4e490fc2342b519439b196307","observation_id":"c7af4cf9-17cc-4399-94c2-4f9e5d9a2b82","resolution":{"observed_at":"2026-08-15T23:30:36.131991Z","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":"2026-08-15T23:30:36.135888Z","title":"L., & Jin , Z","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.135888Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:2db6a96d60f5f03fa7caa520477117c05d97c8eaab25b528245444f4e084beac","observation_id":"b6de39f3-9f88-4d59-9a80-bc3ae75307aa","resolution":{"observed_at":"2026-08-15T23:30:36.135888Z","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":"2026-08-15T23:30:36.139910Z","title":"L., Pan , H.-A., Bluck , A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.139910Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:dd3b81863e739af073404012fcc66eeb0ac18a56a09e1de6332bc84871cefa02","observation_id":"b7346d44-466d-4664-a133-da8898cdaccb","resolution":{"observed_at":"2026-08-15T23:30:36.139910Z","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":"2026-08-15T23:30:36.143658Z","title":"G., & Scalo , J","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.143658Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:cffcce066251bc6171fb9652fddaf35f034256481954ebe4fc15f02f8f52766d","observation_id":"b7e62518-a9d1-44e3-841d-46a614eb6650","resolution":{"observed_at":"2026-08-15T23:30:36.143658Z","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":"2026-08-15T23:30:36.147465Z","title":"1992, title The small-scale density and velocity structure of quiescent molecular clouds , , 257, 715","venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.147465Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:f32e8969da5fa32a7f439d7c0564f936e2ea306035d25f15d126e142b6ef09e6","observation_id":"a2e8e729-4939-4dfb-a95e-98aa1afa1e56","resolution":{"observed_at":"2026-08-15T23:30:36.147465Z","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":"2026-08-15T23:30:36.151322Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.151322Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:89a3d5d65707adfc151b418f72c3c3fabcaa7af5bed30356a40da5a0d2bfdb45","observation_id":"f71c7e71-0b7c-452c-b9ad-6ada870d0bed","resolution":{"observed_at":"2026-08-15T23:30:36.151322Z","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":"2026-08-15T23:30:36.155048Z","title":"2010, PhD thesis, University of Heidelberg, Heidelberg","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.155048Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:3d97a0d67ce6bec7e856dc867ef49bd8dee1cbb9650c1f5f328dec5b6122390d","observation_id":"a75c6bd6-6725-4d9f-94f1-af1669726e00","resolution":{"observed_at":"2026-08-15T23:30:36.155048Z","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":"2026-08-15T23:30:36.158924Z","title":"2013, title The origin of physical variations in the star formation law , , 436, 3167, 10.1093/mnras/stt1799","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.158924Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:6545f34f66091d1f52d25c44ca4f93dc2bf6cc205a661eb738453929768bceba","observation_id":"7745eb78-93b3-4592-92cc-816411400f29","resolution":{"observed_at":"2026-08-15T23:30:36.158924Z","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":"2026-08-15T23:30:36.163501Z","title":"2016, title On the universality of interstellar filaments: theory meets simulations and observations , , 457, 375, 10.1093/mnras/stv2880","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.163501Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:ba0e9816dc768e199c2bf489816add983abb308c403831c35f679e6144a86e68","observation_id":"d95e1680-fe1c-4ac8-876e-aa94c28daf2d","resolution":{"observed_at":"2026-08-15T23:30:36.163501Z","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":"2026-08-15T23:30:36.167383Z","title":null,"venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.167383Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:9306d69fc2e9cdee3cd018e6ab1dda2b2a1a52d168d22a62a2997f1145a73b1f","observation_id":"1a256672-a7c6-41c1-ad4d-ed716e8b7451","resolution":{"observed_at":"2026-08-15T23:30:36.167383Z","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":"2026-08-15T23:30:36.172351Z","title":"S., & Schmidt , W","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.172351Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:3860f4a358ff575257cfb35d5c83c71340aca0ede3e2db0bd8f07ff3cd31ccf5","observation_id":"b22f187e-1c95-4805-b1d5-1d224e97cfb6","resolution":{"observed_at":"2026-08-15T23:30:36.172351Z","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":"2026-08-15T23:30:36.176384Z","title":"M., Longmore , S","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.176384Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:cc758473d51e6fd4cb057c3b54a506f52cde36fa86cb01bb43daeddb0c0c7e25","observation_id":"f28593f1-6328-46e1-bfba-f0ab03073af7","resolution":{"observed_at":"2026-08-15T23:30:36.176384Z","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":"2026-08-15T23:30:36.180438Z","title":"2023, title FIREbox: simulating galaxies at high dynamic range in a cosmological volume , , 522, 3831, 10.1093/mnras/stad1205","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.180438Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:a40ec2e669d2beea3c21240ba4d70763f0be0d4ae320ef2878c5ffbc0ed9da14","observation_id":"3d805331-da52-4816-af4b-3ad7b3655a19","resolution":{"observed_at":"2026-08-15T23:30:36.180438Z","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":"2026-08-15T23:30:36.184412Z","title":"A., Pipher , J","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.184412Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:b2195030cfe44e7a805d63840917acece0e41ab8f8e84aca1c34b87f22b14c2b","observation_id":"922f1cc6-5729-4896-97c9-349df56e5107","resolution":{"observed_at":"2026-08-15T23:30:36.184412Z","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":"2026-08-15T23:30:36.187944Z","title":"J., Allen , L","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.187944Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:f20d16ffbde78f36a385fb965871e66850eff773e0960edacaa4f88c9318ee29","observation_id":"b46fb000-0617-4430-87df-cfc0ba46ab8f","resolution":{"observed_at":"2026-08-15T23:30:36.187944Z","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":"2026-08-15T23:30:36.191643Z","title":"2011, title Analytical Star Formation Rate from Gravoturbulent Fragmentation , , 743, L29, 10.1088/2041-8205/743/2/L29","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.191643Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:5b3622c006bded84ed21bc75fdcee103e6f4bd350b58aac0a4cb529b1981bc29","observation_id":"0b9dd599-9ae2-4d60-8977-b57e449b3a73","resolution":{"observed_at":"2026-08-15T23:30:36.191643Z","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":"2026-08-15T23:30:36.195137Z","title":"2013, title Analytical Theory for the Initial Mass Function","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.195137Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:a8083526af39a416718849c94e02bc5955a3b0c3f3856ab5604f4d721146f58b","observation_id":"431c4dce-2bfd-4baf-9327-fb434c8f7977","resolution":{"observed_at":"2026-08-15T23:30:36.195137Z","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":"2026-08-15T23:30:36.199171Z","title":"H., & Brunt , C","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.199171Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:a6ef92f62448a82f4473a84c23dd917822e203e79fedbea08b3f81f30294a56f","observation_id":"fb00b97a-e42e-44e6-8634-d6aa381d9328","resolution":{"observed_at":"2026-08-15T23:30:36.199171Z","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":"2026-08-15T23:30:36.202875Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.202875Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:1b37470157a3668377f394c31f699a9fd82586979f5323d2864b8009fa8dffb1","observation_id":"ad3be55f-9494-423e-910e-33dec1ae5fa4","resolution":{"observed_at":"2026-08-15T23:30:36.202875Z","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":"2026-08-15T23:30:36.206712Z","title":"F., Quataert , E., & Murray , N","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.206712Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:a3889954911e4ab05c21a17ec029f6e5002a95a0e3a9dd4c21dcf70b7b737ff9","observation_id":"1030c3d6-9a94-4079-9b66-c872199ff63e","resolution":{"observed_at":"2026-08-15T23:30:36.206712Z","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":"2026-08-15T23:30:36.210356Z","title":"F., Wetzel , A., Kere s , D., et al","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.210356Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:6831f6d092b0de9384a323e346671c68435f46a17648848b6c230bdd8d99b87f","observation_id":"fc361bfb-2556-45f2-ad4b-2f7e481b5a12","resolution":{"observed_at":"2026-08-15T23:30:36.210356Z","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":"2026-08-15T23:30:36.214484Z","title":"E., Schinnerer , E., et al","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.214484Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:464227b9bdf8d5079444db894067f54a23a0a44bf54a40ba8bcefd7ec36e07ae","observation_id":"f3665398-406c-4889-aa4a-3067d37cf562","resolution":{"observed_at":"2026-08-15T23:30:36.214484Z","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":"2026-08-15T23:30:36.218169Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.218169Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:ca76e7eb873f6dc0744532bbcf8d4e791f757d903cd235d211ca65e6b3b7d16a","observation_id":"c70b0588-4364-4d26-b435-5077077861fb","resolution":{"observed_at":"2026-08-15T23:30:36.218169Z","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":"2026-08-15T23:30:36.221684Z","title":"C., & Evans , N","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.221684Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:e1e3c623d877603f568cc73b0b9620d7f88081d030288e89f0e3a5242673ab7e","observation_id":"224fb0ae-cf04-4dc3-a096-0d48da00a4b3","resolution":{"observed_at":"2026-08-15T23:30:36.221684Z","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":"2026-08-15T23:30:36.225424Z","title":null,"venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.225424Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:c905ffc6fb7421961e2b0b0466f7d35e67cc060a73cb17eaca1546c491d42f57","observation_id":"d19a7e37-8986-4142-84bd-3c4fe19fdd63","resolution":{"observed_at":"2026-08-15T23:30:36.225424Z","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":"2026-08-15T23:30:36.229143Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.229143Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:9af08c620312b21db0fc73b2c21c4e22073566098c561e9f3bfbfd73608958e0","observation_id":"810d4571-957b-413a-a781-aa8a79b1e641","resolution":{"observed_at":"2026-08-15T23:30:36.229143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.00238","last_updated":"2021-09-01T08:22:41Z","snapshot_observed_at":"2026-08-16T17:59:35.014848Z","submitted_at":"2021-09-01T08:22:41Z","title":"Complexity Measures for Multi-objective Symbolic Regression","version":1},"cited_work":{"arxiv_id":"2109.00238","doi":"10.48550/arxiv.2109.00238","metadata_source":"pith","pith_arxiv_id":"2109.00238","snapshot_observed_at":"2026-08-16T12:16:17.039197Z","title":"Complexity Measures for Multi-objective Symbolic Regression","venue":"cs.LG","work_id":"4cf47ee0-bb8b-4fcc-99cd-b8d9b736e5f8","year":2021},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.232771Z"},"links":{"cited_paper":"/paper/2109.00238","citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:0b0b10bfea59e722a1f77d31b27c699b3c9209711e41ec1cd8ff9858b5ec7290","observation_id":"e1a4365d-3940-4d78-a4d5-b5e42087343f","resolution":{"observed_at":"2026-08-15T23:30:36.873210Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T23:30:36.236794Z","title":"2001, title On the variation of the initial mass function , , 322, 231, 10.1046/j.1365-8711.2001.04022.x","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.236794Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:16d9d676ff841e1f20365e774de4092b87449665ae2a4e33c71c831597d2bced","observation_id":"301d7d79-6412-4c32-8f63-8e9b1af6c65b","resolution":{"observed_at":"2026-08-15T23:30:36.236794Z","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":"2026-08-15T23:30:36.240282Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.240282Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:3c9c443aa89241d30da3555037aa26148051d7766b7cf2edd3de968814bdbd38","observation_id":"6ef8e74f-36d7-494d-9235-5f73b4c58891","resolution":{"observed_at":"2026-08-15T23:30:36.240282Z","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":"2026-08-15T23:30:36.245029Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.245029Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:6ba7a29e9101ea54e1600c68d3f963e8fbd24fd16734807737668fc40f447da2","observation_id":"d6f8b129-af96-40fa-99a6-890e25bd5203","resolution":{"observed_at":"2026-08-15T23:30:36.245029Z","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":"2026-08-15T23:30:36.248719Z","title":"R., Burkhart , B., Forbes , J","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.248719Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:1d409bc1629de212e7e9ff6ba4f3846998140f3cfd40bded373467a058a25d3e","observation_id":"03e5a020-29d7-4c9f-bf1b-d6b64eb037d3","resolution":{"observed_at":"2026-08-15T23:30:36.248719Z","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":"2026-08-15T23:30:36.252427Z","title":"R., Dekel , A., & McKee , C","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.252427Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:71586a99f4630f42e508fc2fb00bdbff794a2ada0ddd72ad0a10ec78e3eb5858","observation_id":"1557a1c9-50f3-4768-8a24-9cca24d913bb","resolution":{"observed_at":"2026-08-15T23:30:36.252427Z","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":"2026-08-15T23:30:36.256069Z","title":"R., & Gnedin , N","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.256069Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:023b587f84cc9fd3b6fd730ae737ab7792f1f09dcd27afce22e8630a3a37ed91","observation_id":"11cf07cc-2f67-43b9-9016-c48ddc4d343a","resolution":{"observed_at":"2026-08-15T23:30:36.256069Z","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":"2026-08-15T23:30:36.259627Z","title":"R., & McKee , C","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.259627Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:361e5cc6b174fe6eaa4365d6d3704afb95ef8a673f3db6090c6e3988255d05ef","observation_id":"286da9a0-2a1c-4bbd-8e4d-f91e50c5a344","resolution":{"observed_at":"2026-08-15T23:30:36.259627Z","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":"2026-08-15T23:30:36.263502Z","title":"R., McKee , C","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.263502Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:adb173c6b2d579355346f0325e3b25d6bafa6cb42eeb20b15ee803b4915775c3","observation_id":"1ed14d67-8918-41db-9d69-304e271de7a3","resolution":{"observed_at":"2026-08-15T23:30:36.263502Z","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":"2026-08-15T23:30:36.267093Z","title":"J., Forbrich , J., Lombardi , M., & Alves , J","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.267093Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:8f9e0c06dfecda4648246b0b6dafdbcff9c32ad08a7e1f57581e19eb89af0fda","observation_id":"6f3a600e-0538-4f15-b54a-525339274139","resolution":{"observed_at":"2026-08-15T23:30:36.267093Z","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":"2026-08-15T23:30:36.270440Z","title":"J., Lombardi , M., & Alves , J","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.270440Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:366b52eb00162ab8a4cbfb97e57f1137e3b6e664ccb2f8d89fb8f3768f04be29","observation_id":"450636ef-a9d2-4328-ae00-8762bd674663","resolution":{"observed_at":"2026-08-15T23:30:36.270440Z","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":"2026-08-15T23:30:36.274069Z","title":null,"venue":null,"work_id":null,"year":1981},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.274069Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:7e7b06d3159cd0e44d8584d15eff43f9ef4faf043c0d27a3583b838e4df14a09","observation_id":"6ee1eca8-be6b-46bc-ba5c-73d15589d523","resolution":{"observed_at":"2026-08-15T23:30:36.274069Z","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":"2026-08-15T23:30:36.277590Z","title":"D., et al","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.277590Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:bfda331ede80669887cf69a9a54d7029c776f4c6a4e6ac3c8b779de6f9cfea66","observation_id":"754252ad-32ef-44a2-b42f-e73d0ef5d357","resolution":{"observed_at":"2026-08-15T23:30:36.277590Z","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":"2026-08-15T23:30:36.281474Z","title":"K., Walter , F., Brinks , E., et al","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.281474Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:f0d27c821051c8757770ee874ce3e0d89f98bac19b4cf80c698237d1cd4d4fa9","observation_id":"74e014e9-f214-4d60-a4ab-a98e7afbea26","resolution":{"observed_at":"2026-08-15T23:30:36.281474Z","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":"2026-08-15T23:30:36.285056Z","title":"K., Walter , F., Sandstrom , K., et al","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.285056Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:da897c628e887278335282f301cf0d2c6ab2854da27de148d963bc3603346719","observation_id":"85a4ef6b-556d-4937-afb2-2f2f744d4570","resolution":{"observed_at":"2026-08-15T23:30:36.285056Z","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":"2026-08-15T23:30:36.288780Z","title":"K., Schinnerer , E., Hughes , A., et al","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.288780Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:538b30d502b9e9c5d200deb177022b5bc72c40f0b0f9dfdb70ead9f742eb2484","observation_id":"6e19cbd4-c4af-47ae-8c8e-032e44bf02ec","resolution":{"observed_at":"2026-08-15T23:30:36.288780Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.07874","last_updated":"2017-11-25T03:53:32Z","snapshot_observed_at":"2026-08-14T20:59:00.743160Z","submitted_at":"2017-05-22T17:38:10Z","title":"A Unified Approach to Interpreting Model Predictions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.07874","snapshot_observed_at":"2026-08-15T23:30:36.292967Z","title":"2017, title A Unified Approach to Interpreting Model Predictions , arXiv e-prints, arXiv:1705.07874, 10.48550/arXiv.1705.07874","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.292967Z"},"links":{"cited_paper":"/paper/1705.07874","citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:2f4984a64499f3889aef0b0b766c52b3cef5712f731d0f4f772eb3e4dfb365da","observation_id":"f9449504-4747-4629-aff1-1c95e3858c92","resolution":{"observed_at":"2026-08-15T23:30:36.292967Z","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":"2026-08-15T23:30:36.297211Z","title":null,"venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.297211Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:cea72a5a5dc54afad5b06290c5038b73621d122e3053d369e72d106a5544190c","observation_id":"b6afc72d-096f-4753-bdec-634eddc4c556","resolution":{"observed_at":"2026-08-15T23:30:36.297211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.11060","last_updated":"2018-06-28T16:19:37Z","snapshot_observed_at":"2026-08-14T18:57:57.107114Z","submitted_at":"2018-06-28T16:19:37Z","title":"Malicious User Experience Design Research for Cybersecurity","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.11060","snapshot_observed_at":"2026-08-15T23:30:36.300785Z","title":"F., & Ostriker , E","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.300785Z"},"links":{"cited_paper":"/paper/1806.11060","citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:140522e142e4a2f4f67ca802de397a8a7648b2be433570e548519acce5c89592","observation_id":"8b00a86d-0a52-4473-bcdf-c1bd9a243d9d","resolution":{"observed_at":"2026-08-15T23:30:36.300785Z","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":"2026-08-15T23:30:36.304671Z","title":"E., Schinnerer , E., Garc \\' a-Burillo , S., et al","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.304671Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:9f32347865df016cb20eaba855f1d49f6e8d23ec6d104268bd24c552e6cc12c1","observation_id":"1cd866ca-bf24-422b-8c51-d63c49d71c25","resolution":{"observed_at":"2026-08-15T23:30:36.304671Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"astro-ph/9801050","last_updated":"1998-01-07T14:06:57Z","snapshot_observed_at":"2026-08-13T02:01:51.367845Z","submitted_at":"1998-01-07T14:06:57Z","title":"Towards a consistent model of the Galaxy: II. Derivation of the model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"astro-ph/9801050","snapshot_observed_at":"2026-08-15T23:30:36.308283Z","title":"1998, title Towards a consistent model of the Galaxy","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.308283Z"},"links":{"cited_paper":"/paper/astro-ph/9801050","citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:386ff89fdb8fba0b8a6da24cd16818732d7e2b7bd2f8486da096e927d8bb265a","observation_id":"29e91312-d297-4f6f-857d-ea0e11b48a4f","resolution":{"observed_at":"2026-08-15T23:30:36.308283Z","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":"2026-08-15T23:30:36.312399Z","title":"Z., Glover , S","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.312399Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:ccc018571ad973ea9eefd09dda3f43cff76a7cb5225c3084eadca3a2d28f0d88","observation_id":"ac8529f3-96fe-4eeb-ac44-aa97fb6bff67","resolution":{"observed_at":"2026-08-15T23:30:36.312399Z","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":"2026-08-15T23:30:36.316452Z","title":"2011, title Star Formation Efficiencies and Lifetimes of Giant Molecular Clouds in the Milky Way , , 729, 133, 10.1088/0004-637X/729/2/133","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.316452Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:b61656bbae8de4c388e23b5b7731f67df39e9a4f5fe83513cbd49f924fed07cf","observation_id":"0ead3745-88d6-4edd-9666-310bd44ae5c3","resolution":{"observed_at":"2026-08-15T23:30:36.316452Z","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":"2026-08-15T23:30:36.320204Z","title":"T., Klein , R","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.320204Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:df4b6387c508cbe60e02a6241d1c04f469e2dd2259fdd262c50c00f49d666a14","observation_id":"29d311dd-fbf0-4bd6-89ad-7ab549c9a597","resolution":{"observed_at":"2026-08-15T23:30:36.320204Z","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":"2026-08-15T23:30:36.324135Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.324135Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:ee0361d096e4c9844a86a71ae92cd881f5636603cd00af0df1a95192aceb5edb","observation_id":"fd9850c3-eefd-4f65-8449-91674eb38a22","resolution":{"observed_at":"2026-08-15T23:30:36.324135Z","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":"10.1088/0004-637x/770/1/49","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:30:36.727456Z","title":null,"venue":null,"work_id":"6e1bb94d-cd09-45f7-839f-eaaca1480753","year":2013},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.327931Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:8d4688fd1a657409e572df143109ec0da22ea5732d6ae8e08d0966b1427bcbfc","observation_id":"76e8ee64-fdae-4284-8604-a3c318dd32fd","resolution":{"observed_at":"2026-08-15T23:30:36.731583Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T23:30:36.331466Z","title":"E., Hayward , C","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.331466Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:6f2ac34f2a5559fd7f1171cd578694bed83ddab0953526a7dcb64ffdc7536935","observation_id":"f36d08c9-97a1-4c07-9b6d-78d67c2197fd","resolution":{"observed_at":"2026-08-15T23:30:36.331466Z","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":"2026-08-15T23:30:36.335525Z","title":"E., Hayward , C","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.335525Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:248f12bf40c59d394a40514f5e1b65f61c0c6aa6739c07178a4d66473b8d1564","observation_id":"8e29ed1f-c76e-4848-85ea-cff8b0f26bf6","resolution":{"observed_at":"2026-08-15T23:30:36.335525Z","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":"2026-08-15T23:30:36.339150Z","title":"C., & Kim , C.-G","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.339150Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:fbae9db4c31bb66e0810857387096b52adddc65675e588ad4e3d47497b9ab51e","observation_id":"a5e3cbaa-ec12-47b2-97e1-66f3f849effc","resolution":{"observed_at":"2026-08-15T23:30:36.339150Z","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":"2026-08-15T23:30:36.342906Z","title":"C., McKee , C","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.342906Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:156e56052c050fd4be16947a11fdfc2713be1f5fcbcca91c731146033895fca2","observation_id":"9be9dd1a-2bd3-43f8-98d4-d3721a5be5a0","resolution":{"observed_at":"2026-08-15T23:30:36.342906Z","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":"2026-08-15T23:30:36.346321Z","title":"C., & Shetty , R","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.346321Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:e38ef9f570c4ea9e432941a5f48a9795bea6ab5ca4324fa6a4898a43eac62313","observation_id":"85d60560-d12c-4af7-a238-4d122184cce7","resolution":{"observed_at":"2026-08-15T23:30:36.346321Z","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":"2026-08-15T23:30:36.349850Z","title":"2022, in American Astronomical Society Meeting Abstracts, Vol","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.349850Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:3c48ba4a74af9b2288160143b4f252a8193c3307ba41640e75536167135ad124","observation_id":"41faa7f8-831f-469f-b831-303f47332620","resolution":{"observed_at":"2026-08-15T23:30:36.349850Z","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":"2026-08-15T23:30:36.353496Z","title":"2002, title The Stellar Initial Mass Function from Turbulent Fragmentation , , 576, 870, 10.1086/341790","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.353496Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:314a611962a59d8340b65cf8e4ea07c7100a21b90fff42b0f263ebe9d31359ed","observation_id":"bc090fde-9dc5-42d9-8dc0-45b0b31497ac","resolution":{"observed_at":"2026-08-15T23:30:36.353496Z","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":"2026-08-15T23:30:36.357591Z","title":"2011, title The Star Formation Rate of Supersonic Magnetohydrodynamic Turbulence , , 730, 40, 10.1088/0004-637X/730/1/40","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.357591Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:9ef4a45a969042fb2c22011fd6674805233333e64cbc7567233d92d35647dc5c","observation_id":"7a10dcc2-e973-42cc-ab94-6ba6d8a83cd8","resolution":{"observed_at":"2026-08-15T23:30:36.357591Z","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":"2026-08-15T23:30:36.360956Z","title":"2018, title Simulating galaxy formation with the IllustrisTNG model , , 473, 4077, 10.1093/mnras/stx2656","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.360956Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:49aae6034c7b47c45cb6261c76811158f31a90b561c93f80d4675e24663e1030","observation_id":"9ac7d688-10f2-4b66-9a95-2fdbc62fb7e0","resolution":{"observed_at":"2026-08-15T23:30:36.360956Z","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":"2026-08-15T23:30:36.364742Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.364742Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:0fbe8b36489cda3cd0fc9e2d5f3a511006dfa64463f56094a701ebff542f029a","observation_id":"b5ad49bb-c9e6-4dda-808e-429884003cf3","resolution":{"observed_at":"2026-08-15T23:30:36.364742Z","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":"2026-08-15T23:30:36.368091Z","title":"S., & Trager , S","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.368091Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:d18c796bb9e5dba3f9baca80ce7f866ccaa81d3281d8b5805a50fe91008314e1","observation_id":"3575cb7b-7c4e-4c27-b757-f4beaf765022","resolution":{"observed_at":"2026-08-15T23:30:36.368091Z","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":"2026-08-15T23:30:36.371739Z","title":"J., & Dame , T","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.371739Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:b300a00494fc74c9a479200b78218456dc627d2120e5275321b7b137832174eb","observation_id":"55084a6e-9456-4ca3-99de-cbee77127dac","resolution":{"observed_at":"2026-08-15T23:30:36.371739Z","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":"10.1088/2041-8205/760/1/l16","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:30:36.648199Z","title":"2012, title Star Formation Laws and Thresholds from Interstellar Medium Structure and Turbulence , , 760, L16, 10.1088/2041-8205/760/1/L16","venue":null,"work_id":"6d4c0f5d-dcdf-4c52-b427-d5bd64d2794d","year":2012},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.375345Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:7b21d5838bf83793862bfdb5a2deb67877a0be9c1e356b74730efd023cc1351f","observation_id":"e9e385da-245b-4e8f-b765-2037a3e7ee85","resolution":{"observed_at":"2026-08-15T23:30:36.652619Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T23:30:36.378738Z","title":"M., Alatalo , K., Federrath , C., Groves , B., & Kewley , L","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":87,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.378738Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:8f7c3e7f419bfd49d7ef0599da52d3b438dd5403ceb324f71d2271499326685c","observation_id":"e52b0561-3ceb-4e66-a3a4-3627b59efd3c","resolution":{"observed_at":"2026-08-15T23:30:36.378738Z","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":"2026-08-15T23:30:36.382294Z","title":"M., Federrath, C., & Kewley, L","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.382294Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:58aff5eadf19af909f91309a676e072a66fbf3d55cebf8287fbaacdacd1558e3","observation_id":"00d9cbee-dd19-43cf-a651-bc6ff482fd68","resolution":{"observed_at":"2026-08-15T23:30:36.382294Z","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":"2026-08-15T23:30:36.385809Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.385809Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:b72759e1fee124fc47feeb44abe6dce2103f4412f2eb010c1094f68fb187e94e","observation_id":"5bcd36e3-313b-40d0-9aee-1f60c7060c21","resolution":{"observed_at":"2026-08-15T23:30:36.385809Z","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":"2026-08-15T23:30:36.389113Z","title":"1959, title The Rate of Star Formation","venue":null,"work_id":null,"year":1959},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.389113Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:6fdb4062f1d6b4549ec67224beea6002671042aadc1d297e23bfaa7af9cd7d90","observation_id":"b4f2e338-b77e-4982-ad50-e493c99098ac","resolution":{"observed_at":"2026-08-15T23:30:36.389113Z","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":"2026-08-15T23:30:36.392580Z","title":"2011, title The link between molecular cloud structure and turbulence , , 529, A1, 10.1051/0004-6361/200913884","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":91,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.392580Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:0d4c540c0b359583247d6754661e3e1c79a7d7ab8439dfa09d96a9e5d11968f6","observation_id":"a1e2aaa2-070d-48d9-836f-ced1afb205e5","resolution":{"observed_at":"2026-08-15T23:30:36.392580Z","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":"2026-08-15T23:30:36.396072Z","title":"2012, title Cluster-formation in the Rosette molecular cloud at the junctions of filaments , , 540, L11, 10.1051/0004-6361/201118566","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.396072Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:f0d6d61fdcb98d606af665dc6a4b022bfcf4ef66ddec5e2dd7020b23709841cc","observation_id":"8cb507c7-587a-492e-b7c6-25926eddc05e","resolution":{"observed_at":"2026-08-15T23:30:36.396072Z","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":"2026-08-15T23:30:36.399508Z","title":"K., Walter , F., et al","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":93,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.399508Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:ef8ddc2010e76f3b0660542cb5ae6d0c6e51523cf9fa793299a8f0da67ca2cfd","observation_id":"ee6e7992-4418-44b6-9ccb-8eff665c3e1e","resolution":{"observed_at":"2026-08-15T23:30:36.399508Z","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/acee6f","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:30:36.600120Z","title":null,"venue":null,"work_id":"94c2969b-49be-4efa-b50e-b72f63206f4e","year":2023},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":94,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.403194Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:2bbdd6c3f6f84a3745c76792c36ae08ad618459d8db9713210e9dab424b06339","observation_id":"bc85ea87-572f-41d6-adda-da77810df59d","resolution":{"observed_at":"2026-08-15T23:30:36.603788Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T23:30:36.406740Z","title":"M., & Dye , S","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":95,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.406740Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:32781da2fbd4ad42125e9c4d55fa33856eb62b694bcfb1fa2c4b5c58566068e3","observation_id":"0d5f26f3-7fa3-410c-85d5-4050de6a289f","resolution":{"observed_at":"2026-08-15T23:30:36.406740Z","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":"2026-08-15T23:30:36.410225Z","title":"M., Rivolo , A","venue":null,"work_id":null,"year":1987},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.410225Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:9753fb71a134d7ac9d37fe9730ed9fb3c394a5324e6f6d849e0c41cf7b140872","observation_id":"3d3a956d-1aa8-4a53-9e45-f6743959e81f","resolution":{"observed_at":"2026-08-15T23:30:36.410225Z","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":"2026-08-15T23:30:36.413972Z","title":"S., & Dav \\'e , R","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":97,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.413972Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:810ed8e5f7e90aadf106841d71e8669ca57c2d0a9b6d075a2d75f5713496b7a8","observation_id":"8ce9ba58-b08e-4b83-9eea-6c00ae5c58be","resolution":{"observed_at":"2026-08-15T23:30:36.413972Z","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":"2026-08-15T23:30:36.417530Z","title":"C., Springel , V., et al","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":98,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.417530Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:b8167e127ed3d195aaa41d49d295e9a2a6e0281553ab0b2d47c4320049562ca5","observation_id":"2689b954-ca8d-442e-a01d-033457727d67","resolution":{"observed_at":"2026-08-15T23:30:36.417530Z","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":"2026-08-15T23:30:36.421474Z","title":"K., Ostriker , E","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":99,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.421474Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:4c73b472be253f9c9a638a8c37056c97c9e056fbbca26f5245d8d405ec627536","observation_id":"e7622d71-626c-4119-925f-a2d19504bf6c","resolution":{"observed_at":"2026-08-15T23:30:36.421474Z","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":"2026-08-15T23:30:36.424920Z","title":"K., Rosolowsky , E., et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression","version":1},"reference_index":100,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:36.424920Z"},"links":{"citing_paper":"/paper/2505.04681"},"observation_digest":"sha256:ec0e4085ed69428ccb4ca2af7008ce209ead3dd133a62d8097a8155d4d371b13","observation_id":"2b04ec8e-b5d2-41e7-a173-de7633ec2348","resolution":{"observed_at":"2026-08-15T23:30:36.424920Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.04681","last_updated":"2025-05-07T18:00:00Z","latest_version":1,"primary_category":"astro-ph.GA","snapshot_observed_at":"2026-08-17T06:28:06.322331Z","submitted_at":"2025-05-07T18:00:00Z","title":"A data-driven approach for star formation parameterization using symbolic regression"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":94,"verified_exact":5,"verified_fuzzy":0},"total_outbound_references":111},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 100 of 111 outbound references and 0 inbound Pith citation observations for arXiv:2505.04681."}