{"as_of":"2026-08-14T22:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:825148a92c9d9282f613b15c23c7c907112f54e008b052e7938bcbd39bd3102a","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":"2026-08-14T06:32:32.682623+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":"2026-07-14T13:24:41.449209Z","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":"2026-07-10T07:36:57.976358Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1109.4371","last_updated":"2015-03-06T01:32:13Z","snapshot_observed_at":"2026-08-13T14:10:01.447330Z","submitted_at":"2011-09-20T17:27:39Z","title":"High dimensional Bayesian inference for Gaussian directed acyclic graph models","version":5},"cited_work":{"arxiv_id":"1109.4371","doi":null,"metadata_source":"pith","pith_arxiv_id":"1109.4371","snapshot_observed_at":"2026-07-10T07:36:57.976358Z","title":"High dimensional Bayesian inference for Gaussian directed acyclic graph models","venue":"math.ST","work_id":"57da0a13-e620-469f-b355-867bef94eebf","year":2011},"citing_paper":{"arxiv_id":"2607.08428","last_updated":"2026-07-09T12:50:29Z","snapshot_observed_at":"2026-08-07T04:07:47.801048Z","submitted_at":"2026-07-09T12:50:29Z","title":"Bayesian DAG Structure Learning with Simultaneous Shrinkage Covariance Estimation under Scale-Mixture Error Distributions in the Proportional High-Dimensional Regime","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-07-10T07:36:34.782211Z"},"links":{"cited_paper":"/paper/1109.4371","citing_paper":"/paper/2607.08428"},"observation_digest":"sha256:736d859bb4c2ff48da0fec161286d8f7ac8cc275c89d504c5df36766eeb249c7","observation_id":"17b57d03-8763-4455-a02a-a8f3c18321b0","resolution":{"observed_at":"2026-07-10T07:36:57.977754Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1109.4371","last_updated":"2015-03-06T01:32:13Z","snapshot_observed_at":"2026-08-13T14:10:01.447330Z","submitted_at":"2011-09-20T17:27:39Z","title":"High dimensional Bayesian inference for Gaussian directed acyclic graph models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1109.4371","snapshot_observed_at":"2026-07-14T13:24:41.449209Z","title":"arXiv:1109.4371","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.10222","last_updated":"2026-07-11T09:22:07Z","snapshot_observed_at":"2026-08-14T17:01:59.043725Z","submitted_at":"2026-07-11T09:22:07Z","title":"Scalable Bayesian structure learning of directed acyclic graphs via Laplace approximation, with an application to breast cancer gene expression networks","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-14T13:24:41.449209Z"},"links":{"cited_paper":"/paper/1109.4371","citing_paper":"/paper/2607.10222"},"observation_digest":"sha256:b992bb1672dc2ae2223b2f689242154cdbd5fcb9ee6de9eb892753dd979927a0","observation_id":"44e2a1f2-6bac-4312-9d0c-5852e2b54f01","resolution":{"observed_at":"2026-07-14T13:24:41.449209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1109.4371/citation-record","integrity":"/paper/1109.4371/integrity","json":"/paper/1109.4371/citation-record.json","paper":"/paper/1109.4371"},"outbound":[],"paper":{"arxiv_id":"1109.4371","last_updated":"2015-03-06T01:32:13Z","latest_version":5,"primary_category":"math.ST","snapshot_observed_at":"2026-08-13T14:10:01.447330Z","submitted_at":"2011-09-20T17:27:39Z","title":"High dimensional Bayesian inference for Gaussian directed acyclic graph models"},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1109.4371."}