{"as_of":"2026-08-15T12:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:96dc450dbbb5a3d1240a268dd6b241e367ff8182db2cf339827de79de6738887","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":"2026-08-15T06:32:42.880941+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":"2026-08-10T14:52:03.237670Z","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":"2026-08-10T14:52:03.618044Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2408.13448","last_updated":"2025-05-30T04:54:27Z","snapshot_observed_at":"2026-08-12T22:58:18.244890Z","submitted_at":"2024-08-24T03:12:21Z","title":"Reinforcement Learning for Causal Discovery without Acyclicity Constraints","version":4},"cited_work":{"arxiv_id":"2408.13448","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.13448","snapshot_observed_at":"2026-08-10T14:52:03.618044Z","title":"Reinforcement Learning for Causal Discovery without Acyclicity Constraints","venue":"cs.LG","work_id":"654926e6-b137-49db-b2c8-c4456e1263e1","year":2024},"citing_paper":{"arxiv_id":"2501.14997","last_updated":"2025-01-25T00:19:38Z","snapshot_observed_at":"2026-08-15T04:01:53.579976Z","submitted_at":"2025-01-25T00:19:38Z","title":"Causal Discovery via Bayesian Optimization","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-10T14:52:03.237670Z"},"links":{"cited_paper":"/paper/2408.13448","citing_paper":"/paper/2501.14997"},"observation_digest":"sha256:0853f33de85e05d2f391b6297aa997136ec641674b76312a5a9606d56518eef5","observation_id":"dd016a03-c0d5-449c-b161-a6ccd0fc8ced","resolution":{"observed_at":"2026-08-10T14:52:03.625059Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2408.13448/citation-record","integrity":"/paper/2408.13448/integrity","json":"/paper/2408.13448/citation-record.json","paper":"/paper/2408.13448"},"outbound":[],"paper":{"arxiv_id":"2408.13448","last_updated":"2025-05-30T04:54:27Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-12T22:58:18.244890Z","submitted_at":"2024-08-24T03:12:21Z","title":"Reinforcement Learning for Causal Discovery without Acyclicity Constraints"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2408.13448."}