{"as_of":"2026-08-17T09:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:244a7a1bbdf40028ad99da68b07409e8d91ac1bf37a831439809eab77cee622a","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":"2026-08-17T06:30:58.91139+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":"2026-08-06T11:23:51.787869Z","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":"2026-08-06T11:24:02.303271Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.03453","last_updated":"2025-08-27T07:44:22Z","snapshot_observed_at":"2026-08-16T12:52:52.780297Z","submitted_at":"2025-03-05T12:35:54Z","title":"Active Learning for Deep Learning-Based Hemodynamic Parameter Estimation","version":2},"cited_work":{"arxiv_id":"2503.03453","doi":null,"metadata_source":"pith","pith_arxiv_id":"2503.03453","snapshot_observed_at":"2026-08-06T11:24:02.303271Z","title":"Active Learning for Deep Learning-Based Hemodynamic Parameter Estimation","venue":"cs.CV","work_id":"a1995fbe-9230-484e-924f-c17de171678f","year":2025},"citing_paper":{"arxiv_id":"2507.22817","last_updated":"2025-07-30T16:32:47Z","snapshot_observed_at":"2026-08-11T22:41:30.914753Z","submitted_at":"2025-07-30T16:32:47Z","title":"Wall Shear Stress Estimation in Abdominal Aortic Aneurysms: Towards Generalisable Neural Surrogate Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T11:23:51.787869Z"},"links":{"cited_paper":"/paper/2503.03453","citing_paper":"/paper/2507.22817"},"observation_digest":"sha256:8e73b91a0191e4524fe81630613aeb6a796d9277eaebb7b141b5358570e66aeb","observation_id":"086892f5-4d5d-4d9e-820f-a0906fabd800","resolution":{"observed_at":"2026-08-06T11:24:02.416649Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2503.03453/citation-record","integrity":"/paper/2503.03453/integrity","json":"/paper/2503.03453/citation-record.json","paper":"/paper/2503.03453"},"outbound":[],"paper":{"arxiv_id":"2503.03453","last_updated":"2025-08-27T07:44:22Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T12:52:52.780297Z","submitted_at":"2025-03-05T12:35:54Z","title":"Active Learning for Deep Learning-Based Hemodynamic Parameter Estimation"},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2503.03453."}