{"as_of":"2026-08-11T06:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3db3c40373d66e6a1f510b372233b20385e700f7b56932f09bad7b3f917177ef","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":"2026-08-10T06:31:04.303077+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":"2026-08-01T15:41:14.739995Z","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":"2026-05-19T09:42:14.060763Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2105.02522","last_updated":"2022-02-03T15:19:54Z","snapshot_observed_at":"2026-08-10T22:02:10.803233Z","submitted_at":"2021-05-06T08:48:02Z","title":"Neural graphical modelling in continuous-time: consistency guarantees and algorithms","version":3},"cited_work":{"arxiv_id":"2105.02522","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2105.02522","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Neural graphical modelling in continuous- time: consistency guarantees and algorithms","venue":null,"work_id":"df71e3f8-f221-47df-83cc-c7d0ca07687d","year":null},"citing_paper":{"arxiv_id":"2506.09816","last_updated":"2026-05-08T09:32:31Z","snapshot_observed_at":"2026-08-06T19:13:56.187847Z","submitted_at":"2025-06-11T14:55:36Z","title":"Identifiability Challenges in Sparse Linear Ordinary Differential Equations","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-19T09:38:17.073391Z"},"links":{"cited_paper":"/paper/2105.02522","citing_paper":"/paper/2506.09816"},"observation_digest":"sha256:ce06613b7ab3bb4b49bd9531faa5f43cd90a6dd71d67bdbbe92d9c38affa6e67","observation_id":"5aac9afe-2136-43f6-b08e-09def9e09d60","resolution":{"observed_at":"2026-05-19T09:42:14.062430Z","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":"2105.02522","last_updated":"2022-02-03T15:19:54Z","snapshot_observed_at":"2026-08-10T22:02:10.803233Z","submitted_at":"2021-05-06T08:48:02Z","title":"Neural graphical modelling in continuous-time: consistency guarantees and algorithms","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.02522","snapshot_observed_at":"2026-08-01T15:41:14.739995Z","title":"arXiv preprint arXiv:2105.02522 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18226","last_updated":"2026-07-20T17:57:45Z","snapshot_observed_at":"2026-08-10T22:02:19.462732Z","submitted_at":"2026-07-20T17:57:45Z","title":"Causal Discovery on Irregular Time Series","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-01T15:41:14.739995Z"},"links":{"cited_paper":"/paper/2105.02522","citing_paper":"/paper/2607.18226"},"observation_digest":"sha256:00afb42d3367f3ffef699a5180e66ca2cacc823aee1e87e292549f0e4bdf28f8","observation_id":"578f6d4d-ee72-496e-ab67-6953046ba51d","resolution":{"observed_at":"2026-08-01T15:41:14.739995Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2105.02522/citation-record","integrity":"/paper/2105.02522/integrity","json":"/paper/2105.02522/citation-record.json","paper":"/paper/2105.02522"},"outbound":[],"paper":{"arxiv_id":"2105.02522","last_updated":"2022-02-03T15:19:54Z","latest_version":3,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-10T22:02:10.803233Z","submitted_at":"2021-05-06T08:48:02Z","title":"Neural graphical modelling in continuous-time: consistency guarantees and algorithms"},"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 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2105.02522."}