{"as_of":"2026-08-09T13:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c4a0618815d1ae22930280a878325790a35db3ab543a8b4db669152eb4b7deaa","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":"2026-08-09T06:31:02.800959+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":"2026-08-05T04:38:44.174114Z","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":"2026-08-05T04:38:45.167050Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2202.12577","last_updated":"2024-04-13T08:24:32Z","snapshot_observed_at":"2026-07-06T12:41:36.793585Z","submitted_at":"2022-02-25T09:32:56Z","title":"Challenges and Opportunities for Machine Learning in Fluid Mechanics","version":3},"cited_work":{"arxiv_id":"2202.12577","doi":null,"metadata_source":"pith","pith_arxiv_id":"2202.12577","snapshot_observed_at":"2026-08-05T04:38:45.167050Z","title":"Challenges and Opportunities for Machine Learning in Fluid Mechanics","venue":"physics.flu-dyn","work_id":"8c8de48e-e006-4551-8283-f46412a00f98","year":2022},"citing_paper":{"arxiv_id":"2509.06041","last_updated":"2025-09-07T13:05:39Z","snapshot_observed_at":"2026-08-09T04:22:42.057398Z","submitted_at":"2025-09-07T13:05:39Z","title":"Multi-Stage Graph Neural Networks for Data-Driven Prediction of Natural Convection in Enclosed Cavities","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T04:38:44.174114Z"},"links":{"cited_paper":"/paper/2202.12577","citing_paper":"/paper/2509.06041"},"observation_digest":"sha256:1df1f26df67828fefac03afa2247de1aa44336a57036abab12d94cb7be24c842","observation_id":"e5cbf24b-e734-4f2a-8a69-5039f07199d6","resolution":{"observed_at":"2026-08-05T04:38:45.238934Z","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/2202.12577/citation-record","integrity":"/paper/2202.12577/integrity","json":"/paper/2202.12577/citation-record.json","paper":"/paper/2202.12577"},"outbound":[],"paper":{"arxiv_id":"2202.12577","last_updated":"2024-04-13T08:24:32Z","latest_version":3,"primary_category":"physics.flu-dyn","snapshot_observed_at":"2026-07-06T12:41:36.793585Z","submitted_at":"2022-02-25T09:32:56Z","title":"Challenges and Opportunities for Machine Learning in Fluid Mechanics"},"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 1 inbound Pith citation observation for arXiv:2202.12577."}