{"as_of":"2026-08-10T10:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a42f7b4594400adb9cc07dc2316681d349d2defe4f9787f1460fda715a818f6a","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:40:20.718959Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-29T09:03:15.602321Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2304.06913","last_updated":"2023-04-14T03:37:30Z","snapshot_observed_at":"2026-07-06T15:15:34.051890Z","submitted_at":"2023-04-14T03:37:30Z","title":"The Random Feature Method for Time-dependent Problems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06913","snapshot_observed_at":"2026-08-06T16:40:20.718959Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12941","last_updated":"2026-07-10T06:47:47Z","snapshot_observed_at":"2026-08-06T16:31:59.298037Z","submitted_at":"2025-07-17T09:29:22Z","title":"Adaptive feature capture method for solving partial differential equations with near singular solutions","version":4},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T16:40:20.718959Z"},"links":{"cited_paper":"/paper/2304.06913","citing_paper":"/paper/2507.12941"},"observation_digest":"sha256:17dcc26e78d869e655f51934908df918605db6bbefaf9b78204fba480620638c","observation_id":"915cd7fb-b22b-4a2b-9b7d-4748c4dc18fb","resolution":{"observed_at":"2026-08-06T16:40:20.718959Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06913","last_updated":"2023-04-14T03:37:30Z","snapshot_observed_at":"2026-07-06T15:15:34.051890Z","submitted_at":"2023-04-14T03:37:30Z","title":"The Random Feature Method for Time-dependent Problems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06913","snapshot_observed_at":"2026-08-05T11:58:19.993179Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02091","last_updated":"2025-09-09T10:01:18Z","snapshot_observed_at":"2026-08-09T12:57:48.010768Z","submitted_at":"2025-09-02T08:42:15Z","title":"CLINN: Conservation Law Informed Neural Network for Approximating Discontinuous Solutions","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T11:58:19.993179Z"},"links":{"cited_paper":"/paper/2304.06913","citing_paper":"/paper/2509.02091"},"observation_digest":"sha256:0bd4cf5242632207b81607c0335c9b691ec2bf97cc7a44ad252eb2b9e1c15354","observation_id":"72fdbe28-871e-4897-8bb4-ef6ca580a230","resolution":{"observed_at":"2026-08-05T11:58:19.993179Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06913","last_updated":"2023-04-14T03:37:30Z","snapshot_observed_at":"2026-07-06T15:15:34.051890Z","submitted_at":"2023-04-14T03:37:30Z","title":"The Random Feature Method for Time-dependent Problems","version":1},"cited_work":{"arxiv_id":"2304.06913","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06913","snapshot_observed_at":"2026-06-29T09:03:15.602321Z","title":"The random feature method for time-dependent problems","venue":null,"work_id":"76cac89a-9547-4aa9-8f25-8e3321b353fa","year":2023},"citing_paper":{"arxiv_id":"2604.25502","last_updated":"2026-04-28T11:04:25Z","snapshot_observed_at":"2026-07-06T23:11:21.433834Z","submitted_at":"2026-04-28T11:04:25Z","title":"A Discrete-Time Random Feature Method for Nonlinear Evolution Equations with Implicit-Explicit Runge--Kutta Time Stepping","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-07T15:44:55.414440Z"},"links":{"cited_paper":"/paper/2304.06913","citing_paper":"/paper/2604.25502"},"observation_digest":"sha256:7bb266068afba0b07ee3be3476bf8bfb91b3b6b84b444892ef3b04d17ac36b28","observation_id":"17f7a18f-97a0-47f9-913d-0fed6e9a8547","resolution":{"observed_at":"2026-05-12T00:11:14.261037Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06913","last_updated":"2023-04-14T03:37:30Z","snapshot_observed_at":"2026-07-06T15:15:34.051890Z","submitted_at":"2023-04-14T03:37:30Z","title":"The Random Feature Method for Time-dependent Problems","version":1},"cited_work":{"arxiv_id":"2304.06913","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06913","snapshot_observed_at":"2026-06-29T09:03:15.602321Z","title":"The random feature method for time-dependent problems","venue":null,"work_id":"76cac89a-9547-4aa9-8f25-8e3321b353fa","year":2023},"citing_paper":{"arxiv_id":"2605.29688","last_updated":"2026-05-28T09:51:54Z","snapshot_observed_at":"2026-08-09T13:52:23.598593Z","submitted_at":"2026-05-28T09:51:54Z","title":"A Novel Tensor Product-Based Neural Network for Solving Partial Differential Equations","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-06-29T09:02:09.817046Z"},"links":{"cited_paper":"/paper/2304.06913","citing_paper":"/paper/2605.29688"},"observation_digest":"sha256:3df0cf3ba99f2ff1cf64c314322d390550418e20028ff2afe0c3480ed639ab2f","observation_id":"bfd82ec2-634b-40f7-9902-5db68fcbecfe","resolution":{"observed_at":"2026-06-29T09:03:15.603812Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06913","last_updated":"2023-04-14T03:37:30Z","snapshot_observed_at":"2026-07-06T15:15:34.051890Z","submitted_at":"2023-04-14T03:37:30Z","title":"The Random Feature Method for Time-dependent Problems","version":1},"cited_work":{"arxiv_id":"2304.06913","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06913","snapshot_observed_at":"2026-06-29T09:03:15.602321Z","title":"The random feature method for time-dependent problems","venue":null,"work_id":"76cac89a-9547-4aa9-8f25-8e3321b353fa","year":2023},"citing_paper":{"arxiv_id":"2605.31027","last_updated":"2026-07-11T04:14:11Z","snapshot_observed_at":"2026-08-02T10:01:28.608360Z","submitted_at":"2026-05-29T08:58:39Z","title":"Multi-Scale Separable Fourier Neural Networks for Solving High-Frequency PDEs","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-28T23:57:43.147283Z"},"links":{"cited_paper":"/paper/2304.06913","citing_paper":"/paper/2605.31027"},"observation_digest":"sha256:bf9c167d9238cef735e83d50f8a4d433460ddda5a21a327000908f76e327631b","observation_id":"80194a85-aaff-402d-b71f-0c1e5907e695","resolution":{"observed_at":"2026-06-29T00:02:49.783069Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2304.06913/citation-record","integrity":"/paper/2304.06913/integrity","json":"/paper/2304.06913/citation-record.json","paper":"/paper/2304.06913"},"outbound":[],"paper":{"arxiv_id":"2304.06913","last_updated":"2023-04-14T03:37:30Z","latest_version":1,"primary_category":"math.NA","snapshot_observed_at":"2026-07-06T15:15:34.051890Z","submitted_at":"2023-04-14T03:37:30Z","title":"The Random Feature Method for Time-dependent Problems"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2304.06913."}