{"as_of":"2026-08-08T16:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:25b630d9df486be4f03b0b6db5ef4293bf1c1b1cb071c0c41aa677503339ab73","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T00:01:46.903756Z","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":"2026-08-06T00:16:16.768632Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2309.15294","last_updated":"2023-10-04T22:53:07Z","snapshot_observed_at":"2026-07-06T16:24:05.806193Z","submitted_at":"2023-09-26T22:15:49Z","title":"Multiple Case Physics-Informed Neural Network for Biomedical Tube Flows","version":2},"cited_work":{"arxiv_id":"2309.15294","doi":"10.48550/arxiv.2309.15294","metadata_source":"pith","pith_arxiv_id":"2309.15294","snapshot_observed_at":"2026-08-06T00:16:16.768632Z","title":"Multiple Case Physics-Informed Neural Network for Biomedical Tube Flows","venue":"physics.flu-dyn","work_id":"6f6fe346-e26d-40d0-916a-b8a303d68846","year":2023},"citing_paper":{"arxiv_id":"2508.04459","last_updated":"2025-08-06T13:59:14Z","snapshot_observed_at":"2026-08-07T20:04:01.982077Z","submitted_at":"2025-08-06T13:59:14Z","title":"Case Studies of Generative Machine Learning Models for Dynamical Systems","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T00:01:46.903756Z"},"links":{"cited_paper":"/paper/2309.15294","citing_paper":"/paper/2508.04459"},"observation_digest":"sha256:b42777d9b88906cdc2f3994003dd145c3a291e9f73c8ae278952689482fa5ffc","observation_id":"1ff17a77-612a-4abb-b701-500fde109e7d","resolution":{"observed_at":"2026-08-06T00:01:47.106075Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2309.15294/citation-record","integrity":"/paper/2309.15294/integrity","json":"/paper/2309.15294/citation-record.json","paper":"/paper/2309.15294"},"outbound":[],"paper":{"arxiv_id":"2309.15294","last_updated":"2023-10-04T22:53:07Z","latest_version":2,"primary_category":"physics.flu-dyn","snapshot_observed_at":"2026-07-06T16:24:05.806193Z","submitted_at":"2023-09-26T22:15:49Z","title":"Multiple Case Physics-Informed Neural Network for Biomedical Tube Flows"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2309.15294."}