{"as_of":"2026-08-09T21:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0e3aaf57b847cadbe59fec41bbcbb3b0a9b110dd1031a0bbf80ab86ce8c5f754","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:26:57.606365Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2506.21776/citation-record","integrity":"/paper/2506.21776/integrity","json":"/paper/2506.21776/citation-record.json","paper":"/paper/2506.21776"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:26:53.322243Z","title":", \" * write output.state after.block = add.period write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:53.322243Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:9743cd3de1d0b37d836fc0e520c63dcd0756b775dda48434df1c6de54fe73b20","observation_id":"2f7beb51-61ab-4875-b8f4-be4d31b5f446","resolution":{"observed_at":"2026-08-06T22:26:53.322243Z","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":"2026-08-06T22:26:53.383378Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:53.383378Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:aff90a6fe685ef81a56c422ed7a20d94e412627bddff04fbdc65db888119189c","observation_id":"97a9bb2d-72cc-4a04-96a6-3ff841835c0f","resolution":{"observed_at":"2026-08-06T22:26:53.383378Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:08.133695Z","title":"Numerical Solution of Ordinary Differential Equations","venue":null,"work_id":"4d876c0a-0de7-4744-9812-436822aea514","year":2009},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:53.427372Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:2661823740e9c80fef6b24af96c51d172a273bf62414d12698299a9d8f926076","observation_id":"2fb13f0f-cd5d-4331-a236-be202a2b6994","resolution":{"observed_at":"2026-08-06T22:27:08.256207Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:07.934692Z","title":"The D eep M ind JAX E cosystem","venue":null,"work_id":"8723768f-c32e-4d34-8579-e8d8f8098c96","year":2020},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:53.492454Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:943d6579fe57f128b7108bfaea4cc29e6cddd3595a8b166dac9cbe52574945e3","observation_id":"51e13d0a-846c-47a4-b90d-62038eb168fb","resolution":{"observed_at":"2026-08-06T22:27:08.051635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:07.734947Z","title":"Gaussian processes for Bayesian estimation in ordinary Differential Equations","venue":null,"work_id":"8f88b62b-5c47-43bd-ba6d-bc8a1dd81a4a","year":2014},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:53.625916Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:4b5401acff683c960d443707ae60a0d0eeb2e3cbadd0459541582a5fa182b3d6","observation_id":"7e39c7fd-e5d6-49ab-877f-66214a2d35e3","resolution":{"observed_at":"2026-08-06T22:27:07.827201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"1973.30969","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:01.701065Z","title":"A Comparison of Discrete Linear Filtering Algorithms","venue":null,"work_id":"d5341c6f-d2f6-465d-9598-a7a80ade7d0e","year":1973},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:53.745020Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:6b85734cbe494666e7270e2ea9cf2c408c5a6aaa03ee862c4d8f31fb067753e8","observation_id":"99fbf190-6ba7-4348-8eed-fd681e2a1c78","resolution":{"observed_at":"2026-08-06T22:27:01.794370Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2105.15183","last_updated":"2022-10-12T09:51:43Z","snapshot_observed_at":"2026-07-06T11:14:31.306862Z","submitted_at":"2021-05-31T17:45:58Z","title":"Efficient and Modular Implicit Differentiation","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.15183","snapshot_observed_at":"2026-08-06T22:26:53.834564Z","title":"Efficient and Modular Implicit Differentiation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:53.834564Z"},"links":{"cited_paper":"/paper/2105.15183","citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:c0c1b32a7d07c1d9bb858481cbcb2512972cccc0ebce37f5876854a32187087a","observation_id":"8a7dde30-bceb-4b30-8f08-cb6e1af8692d","resolution":{"observed_at":"2026-08-06T22:26:53.834564Z","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":"2026-08-06T22:26:53.915197Z","title":"deBInfer: Bayesian inference for dynamical models of biological systems in R","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:53.915197Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:ecf8e94e2f4e1b20acbce15f10a169d7a01c746f12f7135720c8009caebb6ff7","observation_id":"25bf4c6a-2586-468d-920e-dc87c0e2252f","resolution":{"observed_at":"2026-08-06T22:26:53.915197Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:07.588056Z","title":"Calibrated Adaptive Probabilistic ODE Solvers","venue":null,"work_id":"5450dda2-37b5-41bf-97f9-77d5c21f6168","year":2021},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.009035Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:74a08e05ed5533c1b8d1885b39b5f5a440852c39b0929048e809dac20f01e373","observation_id":"b8390253-bc1c-47ab-8fb8-259e9731c4a5","resolution":{"observed_at":"2026-08-06T22:27:07.656918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:07.398669Z","title":"Pick-and-Mix Information Operators for Probabilistic ODE Solvers","venue":null,"work_id":"e2089a0e-4f0a-4a20-be7b-3fe1eca7057a","year":2022},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.100108Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:3afb427d595a571c69ed08857489b53f3ff42905dfe19081a42d6954c150170c","observation_id":"2f015910-ef57-4a97-af39-964510f3f5d7","resolution":{"observed_at":"2026-08-06T22:27:07.504442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:07.110614Z","title":"JAX : composable transformations of P ython+ N um P y programs","venue":null,"work_id":"67f5120f-88f4-400d-8a8e-a7be7ef7e317","year":2018},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.205079Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:54fe72053a1ec328d81b835e4b6ea3e42625bbee38083c3c80cac405c2ba201f","observation_id":"645b1b54-36da-4206-ac19-097e655ba5bd","resolution":{"observed_at":"2026-08-06T22:27:07.285937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:06.872473Z","title":"Numerical Methods for Ordinary Differential Equations","venue":null,"work_id":"c59e7b37-e0ac-4ed3-95d6-7bfabc41bf5f","year":2008},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.286777Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:417ddd96e7cc95afb09781dcc2fb1297c3f69ebd5d5817809e828323bdd13185","observation_id":"3af0514a-7035-4033-bb8b-eb884a644028","resolution":{"observed_at":"2026-08-06T22:27:06.981460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:06.664206Z","title":"Accelerating Bayesian inference over nonlinear differential equations with Gaussian processes","venue":null,"work_id":"3055dd69-b12b-4675-a20f-286c09c12719","year":2009},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.332352Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:9f467d0f1698d0e72875a3112d709e0a5b59163b986e64538b37c247f34e9b02","observation_id":"f45f194d-594a-46d7-af81-545df74cfa50","resolution":{"observed_at":"2026-08-06T22:27:06.756997Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"stable/2324882","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:01.428580Z","title":"Penalized Nonlinear Least Squares Estimation of Time-Varying Parameters in Ordinary Differential Equations","venue":null,"work_id":"a0182e2a-58ce-46d5-94b3-ff4fc9242d31","year":2012},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.391881Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:3727fed90a66e0f82f0e3d490308174e28ed34b347164ca8cd6d3ba5ffe478cf","observation_id":"2ec30676-6788-4e61-9b0b-cd00723d0eb9","resolution":{"observed_at":"2026-08-06T22:27:01.513650Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:06.507258Z","title":"Neural Ordinary Differential Equations","venue":null,"work_id":"3c5927eb-0f43-4637-94c9-cf1c862d1c25","year":2018},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.458322Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:be06c3ef6c8e87cf53f3386637011f253695af00dc674997a6e5ed26fa6b2c8f","observation_id":"8af7619f-8e33-459a-802a-a2b1e20e9e14","resolution":{"observed_at":"2026-08-06T22:27:06.587068Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"euclid.ba/1473276","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:01.178254Z","title":"Bayesian solution uncertainty quantification for differential equations","venue":null,"work_id":"362e9250-235c-4d8d-92aa-6ad967921c1b","year":2016},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.532443Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:0f12f8c12afb1aac667954a9ce979df30bfb695e6ec7562e98439cef6c8ba1ad","observation_id":"09b179b3-42e6-4089-836b-089453e96f8e","resolution":{"observed_at":"2026-08-06T22:27:01.256134Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11222-016-9671-0","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:26:59.146963Z","title":"Statistical analysis of differential equations: introducing probability measures on numerical solutions","venue":null,"work_id":"481a74a9-0172-435e-83fc-0911a895aa52","year":2017},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.642150Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:44219ab17afc8133235d4a5b6943ce8e579772087f911b1fc9dbf3ea5ffde9ed","observation_id":"f7abf5da-bb56-4ed6-b577-c7dc7abcb56c","resolution":{"observed_at":"2026-08-06T22:26:59.289438Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:06.362634Z","title":"simode: Statistical Inference for Systems of Ordinary Differential Equations using Separable Integral-Matching","venue":null,"work_id":"3005c556-563e-4f80-97ef-c7992bf3cbe4","year":2020},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:54.877152Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:52ef70658ea4d315a8310ef27bdac196a52475e97e73a5c0b4302fe3b53f9603","observation_id":"ce1c20d6-9b15-4047-965e-1362578e5b42","resolution":{"observed_at":"2026-08-06T22:27:06.428646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:06.197606Z","title":"Bayesian numerical analysis","venue":null,"work_id":"a5636ec3-6fec-4a7a-9260-1da5b97ffe5f","year":1988},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.042648Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:45da7c76f3c42ed21394fc1b5ac35d2a20577b7df63d6072e06daa65fcd6f67c","observation_id":"2232704c-81d0-440c-a30a-ae32c4cf0fc2","resolution":{"observed_at":"2026-08-06T22:27:06.275934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:06.019983Z","title":"ODE parameter inference using adaptive gradient matching with Gaussian processes","venue":null,"work_id":"1f297152-c6ad-4598-90b0-546cc4bfa55b","year":2013},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.097291Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:e36b7833e62ad687871144c555c93a6b61931405a87892f0549b0a983f492f08","observation_id":"f6999eb9-ca13-491a-bb32-8461117ff203","resolution":{"observed_at":"2026-08-06T22:27:06.081383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:05.828466Z","title":"A family of embedded Runge - Kutta formulae","venue":null,"work_id":"824c6afc-4812-4b42-828b-f1ac7fe0e4e7","year":1980},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.137268Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:0ff61e53d99c45fc1fb592e0862c796e21f46e0464f96e57f24eded1ff9e6839","observation_id":"18cedcde-a538-4f6d-bfe1-fc0718095166","resolution":{"observed_at":"2026-08-06T22:27:05.891695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T22:26:55.176103Z","title":"Hybrid Monte Carlo","venue":null,"work_id":null,"year":1987},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.176103Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:b17230bd22e3d8661cd6a0bc258583bfbb4e145f18035df21a6c377a6e34d55e","observation_id":"28fd7740-fcdd-4c4e-972a-93fc38fa87a7","resolution":{"observed_at":"2026-08-06T22:26:55.176103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:05.667595Z","title":"Bayesian Data Analysis","venue":null,"work_id":"d94f8ab6-01aa-49aa-b61f-8c193e51bb84","year":2013},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.236164Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:709c1136255de36d827576affb7907ff14686b5e40d3d1e577b98c632821c090","observation_id":"8b5441db-c318-4c3b-9588-dc019cf801c7","resolution":{"observed_at":"2026-08-06T22:27:05.748714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11222-016-9643-4","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:26:58.942672Z","title":"Fast approximate Bayesian computation for estimating parameters in differential equations","venue":null,"work_id":"d05a2b5b-cf78-4496-a862-7b5523791022","year":2017},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.325022Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:74549abe9b01b2dc846efc76b7cad75b4869441b44486e07aa3583a56fd8f726","observation_id":"d2603d36-148e-4627-8ae0-3137d705a688","resolution":{"observed_at":"2026-08-06T22:26:59.023566Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2019.88523","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:00.768930Z","title":"Mixed Variational Inference","venue":null,"work_id":"644d3f6a-c295-4845-b9a5-23ff345f7c31","year":2019},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.397366Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:f5d0d4629c47f5c994f6f1e7f2a66e5d5252d6f611e5d44f35d4c3f4a3ff1087","observation_id":"2e195455-09a6-412b-819e-a57e6ff7d9eb","resolution":{"observed_at":"2026-08-06T22:27:00.864948Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:05.516198Z","title":"Scalable variational inference for dynamical systems","venue":null,"work_id":"da642c10-4a89-4fd0-86b3-b961002d35cb","year":2017},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.485193Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:d05ad0062371d046a0acca70db7f2380c08805c62fef1f7270e62b294a71ec46","observation_id":"a1c224a1-c2b7-49a4-bf84-5bad75dc6aae","resolution":{"observed_at":"2026-08-06T22:27:05.589597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:05.350259Z","title":"Numerical Methods for Ordinary Differential Equations: Initial Value Problems","venue":null,"work_id":"3983f241-9a27-4724-a1c5-5f23c230c1b8","year":2010},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.558693Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:8e4548bd88bc35ac4161322ca79076ef923d5acdf5b155b1568c850f737d4f83","observation_id":"dd6466ed-f65c-4c68-8431-6084685771f0","resolution":{"observed_at":"2026-08-06T22:27:05.417769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T22:26:55.628314Z","title":"Array programming with NumPy","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.628314Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:4af8980b2de0605a26dd775cd19778f13d5f002a8b68906ac3767107178ed1a4","observation_id":"b88bdd5f-da32-48fe-a7c3-89498be76684","resolution":{"observed_at":"2026-08-06T22:26:55.628314Z","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":"2026-08-06T22:26:55.701321Z","title":"Probabilistic numerics and uncertainty in computations","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.701321Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:bd0f9329ab81b3de63abfad3a2b5d6a8450914e25cd34e066d23a5b222f0ca06","observation_id":"a96d4cdd-91cb-47cc-9c06-d363bbe4728c","resolution":{"observed_at":"2026-08-06T22:26:55.701321Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:05.189203Z","title":"ODEPACK , a systematized collection of ODE solvers","venue":null,"work_id":"9cdd504f-cdc5-4c95-a76a-83e7835ddc38","year":1983},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.779170Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:9c399fe65363950d642014dd3590215fff742191188688990f5baa45f2127961","observation_id":"af41ec3a-a170-4c93-b480-7433be56f098","resolution":{"observed_at":"2026-08-06T22:27:05.254948Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18637/jss.v075.i02","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:26:58.831523Z","title":"CollocInfer: Collocation Inference in Differential Equation Models","venue":null,"work_id":"8b9e896e-f613-4e33-a3fa-21916f5eb157","year":2016},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.820370Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:3472811470c332ce2e6e899080ea7e56e1f9e4eece7b8d37006bcff3bb9ef192","observation_id":"2d5cd628-57d0-4d2f-b38a-406055fef0dd","resolution":{"observed_at":"2026-08-06T22:26:58.884509Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"1971.10998","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:00.238698Z","title":"Discrete square root filtering: A survey of current techniques","venue":null,"work_id":"6f2a9339-3d3e-4362-a757-2adc23c93306","year":1971},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.857233Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:aa6a77482ff1c5d518a6cc493a5f9f3b4d676e21a3b2646f4b6d54242e024a2e","observation_id":"635f99d0-ee1a-4ab1-96d7-582b1fa0d3a3","resolution":{"observed_at":"2026-08-06T22:27:00.445692Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:05.038055Z","title":"Active uncertainty calibration in Bayesian ODE solvers","venue":null,"work_id":"4352cb13-cac1-4d04-bae8-be0ed7fc6a8b","year":2016},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.889134Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:a7e9e9d4636bc5c55bcfbf294314e47c47ac03fd37779410980f81b0388d65a8","observation_id":"28aa684e-f31e-4ff5-8bba-07040515042f","resolution":{"observed_at":"2026-08-06T22:27:05.113187Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:04.853524Z","title":"Differentiable Likelihoods for Fast Inversion of Likelihood-Free Dynamical Systems","venue":null,"work_id":"e547713d-86a1-4b4f-bc37-828d8ed77352","year":2020},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.928247Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:8cb44a102e8ed9249a60883f743e783cdde500acdc49e73e5878682eadc96dc3","observation_id":"e92a39fa-9d27-4ca3-9dc5-9b1e76d0a3f8","resolution":{"observed_at":"2026-08-06T22:27:04.934848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11222-020-09972-4","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:26:58.669145Z","title":"Convergence rates of Gaussian ODE filters","venue":null,"work_id":"293bc297-18b7-4425-9c04-5b83beffc9e0","year":2020},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:55.979786Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:0346a7a1acd8a57b834ec5ef6f3daf24fe9993d4d61adb7d0838291d0c03e916","observation_id":"ded4fe21-19fd-436e-b06d-803053fa33c3","resolution":{"observed_at":"2026-08-06T22:26:58.762285Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.02435","last_updated":"2022-02-04T23:32:29Z","snapshot_observed_at":"2026-08-09T19:02:16.039793Z","submitted_at":"2022-02-04T23:32:29Z","title":"On Neural Differential Equations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.02435","snapshot_observed_at":"2026-08-06T22:26:56.020631Z","title":"On Neural Differential Equations","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.020631Z"},"links":{"cited_paper":"/paper/2202.02435","citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:f9769e90529027bc299d5492f0ecc68cff3e48725ff5c5f021cc03b6adeac811","observation_id":"dfc58300-471f-41cb-905e-48d9e94e3d74","resolution":{"observed_at":"2026-08-06T22:26:56.020631Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:04.681745Z","title":"Probabilistic ODE solutions in millions of dimensions","venue":null,"work_id":"6e03683d-0dc4-447f-8b9e-51ef9929fb38","year":2021},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.096877Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:fa7336f95245b44b5907394e676fb95a7b2c7112d4e7a026114652a83d78cfb6","observation_id":"f5fd3c0c-c1af-4b85-9e63-f903c68805c8","resolution":{"observed_at":"2026-08-06T22:27:04.756907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.10106","last_updated":"2020-12-18T08:35:36Z","snapshot_observed_at":"2026-08-08T12:51:46.025116Z","submitted_at":"2020-12-18T08:35:36Z","title":"Stable Implementation of Probabilistic ODE Solvers","version":1},"cited_work":{"arxiv_id":"2012.10106","doi":"10.48550/arxiv.2012.10106","metadata_source":"pith","pith_arxiv_id":"2012.10106","snapshot_observed_at":"2026-08-07T06:16:28.064256Z","title":"Stable Implementation of Probabilistic ODE Solvers","venue":"stat.ML","work_id":"ee4252cf-47a8-4011-862e-c0c0b9adf100","year":2020},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.131864Z"},"links":{"cited_paper":"/paper/2012.10106","citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:f36162c419fdde3370c42ea64a1dc66daf94d3be0709fe3aaca5d912abcf4087","observation_id":"0f9e804b-4b33-4ff3-9daa-6a9ae5f97619","resolution":{"observed_at":"2026-08-06T22:26:58.569372Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:04.496619Z","title":"a mer PN (2024). Implementing probabilistic numerical solvers for differential equations. Ph.D. thesis, Universit \\","venue":null,"work_id":"f4d6cdf2-c6e4-4f03-b588-953efcef1258","year":2024},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.202086Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:39ec9c7a171368f66e2d40bd87fc68a7eec29831d33e7973623799d3bfc2b903","observation_id":"ac271756-eefd-4e47-b541-689da455c724","resolution":{"observed_at":"2026-08-06T22:27:04.589899Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:04.298874Z","title":"B lackjax: A sampling library for JAX","venue":null,"work_id":"488b69c2-c2b2-49c0-bd19-a9f677c7ba47","year":2020},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.265162Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:0a1ace2f2acb5c06fcd8124c3e71d3e0e25b5a0ab8474d06e2cd232c9d2c04ff","observation_id":"7ca8da7b-7805-4e82-8593-db81a68078de","resolution":{"observed_at":"2026-08-06T22:27:04.403507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:04.068896Z","title":"Multiphase MCMC sampling for parameter inference in nonlinear ordinary differential equations","venue":null,"work_id":"ede80e21-91e3-4976-85ee-fe8e22396f0c","year":2018},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.325476Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:d5d56db52105484f8d99dbd47c0b2c93c74c43f1d2bf1a9154d73410144da946","observation_id":"8858e887-55ec-4dff-99d3-2b7a4003fd25","resolution":{"observed_at":"2026-08-06T22:27:04.158949Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:03.847164Z","title":"deGradInfer: Parameter Inference for Systems of Differential Equation","venue":null,"work_id":"12315083-6731-47d9-837b-56ca98aadcec","year":2020},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.429765Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:ac34b762e3cff31061d240a2e0f552b03b0ddc9efcfcb06939830c40d3fea08b","observation_id":"347ed4ca-f691-440c-99d6-de72a0a837aa","resolution":{"observed_at":"2026-08-06T22:27:03.938620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T22:26:56.520518Z","title":"A Practical Bayesian Framework for Backpropagation Networks","venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.520518Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:670a692aeca16714779480faf08a52c001a8c1e75fd38bb52b9e1c60d6e6c6b7","observation_id":"0439939a-f077-44de-9003-872b5d9fa82b","resolution":{"observed_at":"2026-08-06T22:26:56.520518Z","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":"2026-08-06T22:26:56.562507Z","title":"Bayesian estimation of time-varying parameters in ordinary differential equation models with noisy time-varying covariates","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.562507Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:fbeb82686fae2e2608038a76913d3bcb4032823511ba0abb1e911bf18c763ca0","observation_id":"5209c837-d555-4a77-87eb-d4f7da59aab3","resolution":{"observed_at":"2026-08-06T22:26:56.562507Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s00180-020-01014-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:26:58.357305Z","title":"R package for statistical inference in dynamical systems using kernel based gradient matching: KGode","venue":null,"work_id":"c3dbe23a-8c1d-4152-a005-8a5f8213d059","year":2021},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.616443Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:c6e934b9ddd2e5a290b8927c987168a73d513873a210b34cee54d3a6c4ce1ed3","observation_id":"c377fdda-e17e-4cde-ba59-9ecaecec5df9","resolution":{"observed_at":"2026-08-06T22:26:58.393407Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:03.634769Z","title":"Numerical Optimization","venue":null,"work_id":"df39035a-fe1e-4225-bbc9-004b2f19c264","year":2006},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.663120Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:ae5a60fb65fdc2d02979eef18037fbce4da8306d5e85db24f8995857b401cd47","observation_id":"587a8385-125f-4496-a1a4-a4d646c97bb7","resolution":{"observed_at":"2026-08-06T22:27:03.716276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:03.427671Z","title":"Automatic selection of methods for solving stiff and nonstiff systems of ordinary differential equations","venue":null,"work_id":"506f993c-bd04-4e1b-8364-fa1fc2a2175e","year":1983},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.723433Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:aca3fd6a11849ce0ee51671d6d824009974d01f1b51a11f7f475b17cabb240c9","observation_id":"b8c001bc-f04e-4660-b91c-bde938bcdb49","resolution":{"observed_at":"2026-08-06T22:27:03.505507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1101/2020.04.21.20073536","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:26:58.201470Z","title":"Multi-Level Modeling of Early COVID -19 Epidemic Dynamics in French Regions and Estimation of the Lockdown Impact on Infection Rate","venue":null,"work_id":"885c084a-eae6-4b16-a488-59a42b5dc036","year":2020},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.757380Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:3e56780f11e5ab0d50a1ff7d8e5417a37644b9ceb9bb08382adb52e8436db3ee","observation_id":"b053cead-ca7f-432b-aad8-f5aa351732dc","resolution":{"observed_at":"2026-08-06T22:26:58.262110Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:03.273080Z","title":"Probabilistic ODE solvers with Runge - Kutta means","venue":null,"work_id":"cf970428-3191-47a6-9dd4-0819391a5f96","year":2014},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.800430Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:99d267f4d8cbfa895bc3939b6265493a8ffaa3da9823503bc31c3b664cc831de","observation_id":"3bf97dd3-4480-4fcc-980f-ef6507e6cf5d","resolution":{"observed_at":"2026-08-06T22:27:03.355029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T22:26:56.845397Z","title":"A probabilistic model for the numerical solution of initial value problems","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.845397Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:ddb46fbfadaf3e5b99267f31054d663fbe81a0bc81b6e605d6882d4ae8c53071","observation_id":"aa498f1e-499c-4987-bd63-f0ab258a5d5d","resolution":{"observed_at":"2026-08-06T22:26:56.845397Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-1-4614-7320-6_147-1","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:03:56.115653Z","title":"FitzHugh--Nagumo Model , pp","venue":"Encyclopedia of Computational Neuroscience","work_id":"ba3c3b30-cb91-44d1-835c-9d93921a64d1","year":2013},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.880413Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:ba38ab4cecc5e20b2e7d4883cb468a98fe879074ca878e517e09afd104fd4ecf","observation_id":"7a0ed493-c5f8-4046-b0f9-893dce9fa5ce","resolution":{"observed_at":"2026-08-06T22:26:58.095383Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-94-017-2219-3_2","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:03:45.533247Z","title":"Bayesian solution of ordinary differential equations","venue":null,"work_id":"1b9124e0-59eb-46b9-9463-c32b528f0714","year":1992},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.921798Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:74b39910a8e02ee293e930765ecb821c8fc2023f965b5a566e122d52c039900b","observation_id":"684b5d36-8bcd-445a-bf4d-cbd80e9b2938","resolution":{"observed_at":"2026-08-06T22:26:57.878392Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:03.137911Z","title":"Stan Modeling Language Users Guide and Reference Manual","venue":null,"work_id":"89d9d301-e363-4d52-91d4-275a94d9e8a3","year":2023},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:56.976337Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:849b516891a6f4093b906023fbbeaa59087bff9892f44fc5bf393ad578892e5c","observation_id":"a757a2b7-a7ad-4c63-8e7c-9450edf3b190","resolution":{"observed_at":"2026-08-06T22:27:03.197770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:02.908364Z","title":"Probabilistic linear multistep methods","venue":null,"work_id":"8c1c0cf2-d7a1-4ba1-a105-8247556bcaa4","year":2016},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:57.046342Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:5ad8ad78db9dbefba043ca49992b6b5a869655dbd9637263ae27e74f7aa3f1fc","observation_id":"8370308b-031c-4de2-bad8-9ac241f2e798","resolution":{"observed_at":"2026-08-06T22:27:03.029007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:02.734935Z","title":"Fenrir : Physics-Enhanced Regression for Initial Value Problems","venue":null,"work_id":"23ff0161-f139-418a-ae8b-73398b0ca80b","year":2022},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:57.125213Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:47ebdf9c422049f47ff0e935bf55c3184478cba39a36c8b49c0ecf219335f997","observation_id":"e9a7097a-f877-42d5-ac0d-016fd97fb8f3","resolution":{"observed_at":"2026-08-06T22:27:02.814774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.03440","last_updated":"2019-04-24T09:13:11Z","snapshot_observed_at":"2026-08-09T07:35:00.523582Z","submitted_at":"2018-10-08T13:36:24Z","title":"Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective","version":4},"cited_work":{"arxiv_id":"1810.03440","doi":null,"metadata_source":"pith","pith_arxiv_id":"1810.03440","snapshot_observed_at":"2026-08-06T22:26:59.734478Z","title":"Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective","venue":"stat.ME","work_id":"2a8efe7d-acd4-44d9-acd6-8f89b5e156c6","year":2018},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:57.198371Z"},"links":{"cited_paper":"/paper/1810.03440","citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:6a5bd033e569686fffee81b4e5e9a3630017ce28e9acf202bb9fb291592f8c71","observation_id":"e321abb1-3963-4c6f-acab-800fa4172349","resolution":{"observed_at":"2026-08-06T22:26:59.897567Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T22:26:57.242993Z","title":"Bayesian ODE solvers: the maximum a posteriori estimate","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:57.242993Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:c5329ad356f24e218b3fc859479bcc70927f31f7580e0661b8e0713e91cc724f","observation_id":"45e8035e-3fbf-4947-837d-8ec9f285d07a","resolution":{"observed_at":"2026-08-06T22:26:57.242993Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:02.546511Z","title":"pCODE: Estimation of an Ordinary Differential Equation Model by Parameter Cascade Method","venue":null,"work_id":"01164cc5-5b28-4c8d-b30c-a36c836b98f6","year":2022},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:57.305470Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:949d5b06c58b62fc34dd250b052a1c3b9a73f7ec6f8df2f69cdf8bbb76357474","observation_id":"401e3709-b12c-44b6-8ba5-76e38dcc86c0","resolution":{"observed_at":"2026-08-06T22:27:02.645412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.02100","last_updated":"2021-12-03T07:20:50Z","snapshot_observed_at":"2026-07-06T12:15:10.261296Z","submitted_at":"2021-12-03T07:20:50Z","title":"ProbNum: Probabilistic Numerics in Python","version":1},"cited_work":{"arxiv_id":"2112.02100","doi":null,"metadata_source":"pith","pith_arxiv_id":"2112.02100","snapshot_observed_at":"2026-08-06T22:26:59.508188Z","title":"ProbNum: Probabilistic Numerics in Python","venue":"cs.MS","work_id":"50e63d25-2ff1-42f5-84f5-f4ba1d6f8b8e","year":2021},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:57.361446Z"},"links":{"cited_paper":"/paper/2112.02100","citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:9bce5c23d01706874e26ca9bbbe8163c530a6bbb20ce7a71c04a09754bb43090","observation_id":"3c5a798f-bece-470f-bb14-81e9453e8332","resolution":{"observed_at":"2026-08-06T22:26:59.595483Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:02.247511Z","title":"Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs","venue":null,"work_id":"538b9cff-d679-4b36-a8a6-80982c606c1a","year":2019},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:57.436482Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:f3f07e00eb2de241dcf81d975baef96ea5902c588832d95fdcd125f09682bab0","observation_id":"68fdb94c-6b86-47fd-93fd-d1bbb88837a3","resolution":{"observed_at":"2026-08-06T22:27:02.424283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:27:01.930410Z","title":"Data-Adaptive Probabilistic Likelihood Approximation for Ordinary Differential Equations","venue":null,"work_id":"0f692091-8a31-4dd2-874c-696c591cc67a","year":2024},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:57.522310Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:a3cf95e38aca365af3ed12ab01647efa753454ef838431639af23213df8f1668","observation_id":"3114de77-09d9-4906-9bb8-b9ee63a77a56","resolution":{"observed_at":"2026-08-06T22:27:02.102597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1073/pnas.2020397118","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:26:57.699109Z","title":"Inference of dynamic systems from noisy and sparse data via manifold-constrained Gaussian processes","venue":null,"work_id":"44bd8565-653a-4848-b330-5f730b0a8ef0","year":2021},"citing_paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-06T22:26:57.606365Z"},"links":{"citing_paper":"/paper/2506.21776"},"observation_digest":"sha256:531115db0d0f6c0a9e31dd092021a324d9ba8087de5e89f4a841750640532140","observation_id":"e3755a42-137e-4697-820c-d83400676216","resolution":{"observed_at":"2026-08-06T22:26:57.737703Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.21776","last_updated":"2025-06-26T21:22:43Z","latest_version":1,"primary_category":"stat.CO","snapshot_observed_at":"2026-08-09T19:03:33.567857Z","submitted_at":"2025-06-26T21:22:43Z","title":"rodeo: Probabilistic Methods of Parameter Inference for Ordinary Differential Equations"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":1,"metadata_mismatch":3,"parse_uncertain":0,"unresolved":12,"verified_exact":13,"verified_fuzzy":33},"total_outbound_references":62},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2506.21776."}