{"as_of":"2026-08-09T23:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1c2a373780e9a6dd97c88aed62b7b352317fe6563de4593c70c24b431091a459","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:48:58.581429Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T11:26:03.414870Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.07929","last_updated":"2024-12-10T21:18:08Z","snapshot_observed_at":"2026-08-08T20:57:32.698174Z","submitted_at":"2024-12-10T21:18:08Z","title":"Dirichlet-Neumann Averaging: The DNA of Efficient Gaussian Process Simulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.07929","snapshot_observed_at":"2026-08-07T11:48:58.581429Z","title":"Dirichlet-neumann averaging: The dna of efficient gaussian process simulation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01644","last_updated":"2025-06-08T17:42:46Z","snapshot_observed_at":"2026-08-07T11:34:24.638263Z","submitted_at":"2025-06-02T13:17:23Z","title":"A Budgeted Multi-Level Monte Carlo Method for Full Field Estimates of Multi-PDE Problems","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:48:58.581429Z"},"links":{"cited_paper":"/paper/2412.07929","citing_paper":"/paper/2506.01644"},"observation_digest":"sha256:13da9785cea4d53c345c713e7afa3210a059ca8d21469a004e3700ab8af343b4","observation_id":"0c37fb79-f8f8-4024-b00f-6cf033ad09e5","resolution":{"observed_at":"2026-08-07T11:48:58.581429Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.07929","last_updated":"2024-12-10T21:18:08Z","snapshot_observed_at":"2026-08-08T20:57:32.698174Z","submitted_at":"2024-12-10T21:18:08Z","title":"Dirichlet-Neumann Averaging: The DNA of Efficient Gaussian Process Simulation","version":1},"cited_work":{"arxiv_id":"2412.07929","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.07929","snapshot_observed_at":"2026-08-07T11:26:03.414870Z","title":"Dirichlet-Neumann Averaging: The DNA of Efficient Gaussian Process Simulation","venue":"stat.CO","work_id":"511621ba-b761-436b-b963-ebd4beb8738f","year":2024},"citing_paper":{"arxiv_id":"2506.02647","last_updated":"2026-06-22T13:41:27Z","snapshot_observed_at":"2026-08-07T11:17:02.279650Z","submitted_at":"2025-06-03T09:00:43Z","title":"Multilevel Stochastic Gradient Descent for Optimal Control Under Uncertainty","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:25:58.785808Z"},"links":{"cited_paper":"/paper/2412.07929","citing_paper":"/paper/2506.02647"},"observation_digest":"sha256:4582e35c1f936bab333131e5ef0d74575927da54091d7f79339d8e6acf8c501d","observation_id":"6b86e101-cd62-446e-843a-793927eeb41d","resolution":{"observed_at":"2026-08-07T11:26:03.554210Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2412.07929/citation-record","integrity":"/paper/2412.07929/integrity","json":"/paper/2412.07929/citation-record.json","paper":"/paper/2412.07929"},"outbound":[],"paper":{"arxiv_id":"2412.07929","last_updated":"2024-12-10T21:18:08Z","latest_version":1,"primary_category":"stat.CO","snapshot_observed_at":"2026-08-08T20:57:32.698174Z","submitted_at":"2024-12-10T21:18:08Z","title":"Dirichlet-Neumann Averaging: The DNA of Efficient Gaussian Process Simulation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.07929."}