{"as_of":"2026-08-09T14:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:96ce111faf1b62ee9a45b4349dc3995fbb4e259ce16173d97e60f5c2d2f063ac","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":"2026-08-09T06:31:02.800959+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":"2026-08-07T10:48:05.631118Z","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":"2026-08-06T17:11:32.755518Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2106.03646","last_updated":"2022-09-09T17:37:17Z","snapshot_observed_at":"2026-07-06T11:16:43.669732Z","submitted_at":"2021-06-07T14:18:45Z","title":"Proximal nested sampling for high-dimensional Bayesian model selection","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.03646","snapshot_observed_at":"2026-08-07T10:48:05.631118Z","title":"D., Pereyra M., 2021, @doi [arXiv e-prints] 10.48550/arXiv.2106.03646 , https://ui.adsabs.harvard.edu/abs/2021arXiv210603646C p","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.04339","last_updated":"2025-06-04T18:00:24Z","snapshot_observed_at":"2026-08-08T15:17:40.435844Z","submitted_at":"2025-06-04T18:00:24Z","title":"Savage-Dickey density ratio estimation with normalizing flows for Bayesian model comparison","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T10:48:05.631118Z"},"links":{"cited_paper":"/paper/2106.03646","citing_paper":"/paper/2506.04339"},"observation_digest":"sha256:f32b3a685032724e1aa344bd973c35160567756f5d8f90486fe76181ef117223","observation_id":"6814f08c-0523-4004-a46f-b46410c8bd13","resolution":{"observed_at":"2026-08-07T10:48:05.631118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.03646","last_updated":"2022-09-09T17:37:17Z","snapshot_observed_at":"2026-07-06T11:16:43.669732Z","submitted_at":"2021-06-07T14:18:45Z","title":"Proximal nested sampling for high-dimensional Bayesian model selection","version":3},"cited_work":{"arxiv_id":"2106.03646","doi":null,"metadata_source":"pith","pith_arxiv_id":"2106.03646","snapshot_observed_at":"2026-08-06T17:11:32.755518Z","title":"Proximal nested sampling for high-dimensional Bayesian model selection","venue":"stat.ME","work_id":"46d525e4-bc25-4433-b26c-0a73d0e9b59e","year":2021},"citing_paper":{"arxiv_id":"2507.11699","last_updated":"2025-07-15T20:07:02Z","snapshot_observed_at":"2026-08-06T17:01:40.796763Z","submitted_at":"2025-07-15T20:07:02Z","title":"Granulation signatures in 3D hydrodynamical simulations: evaluating background model performance using a Bayesian nested sampling framework","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T17:11:32.316457Z"},"links":{"cited_paper":"/paper/2106.03646","citing_paper":"/paper/2507.11699"},"observation_digest":"sha256:23b640e87a84ce21b8e97b18b587fdc9dc3ea2ff49af9cb2535deda3f4d23ab1","observation_id":"d9f5b9f7-f491-43ae-b118-b98c44194f9f","resolution":{"observed_at":"2026-08-06T17:11:32.762017Z","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/2106.03646/citation-record","integrity":"/paper/2106.03646/integrity","json":"/paper/2106.03646/citation-record.json","paper":"/paper/2106.03646"},"outbound":[],"paper":{"arxiv_id":"2106.03646","last_updated":"2022-09-09T17:37:17Z","latest_version":3,"primary_category":"stat.ME","snapshot_observed_at":"2026-07-06T11:16:43.669732Z","submitted_at":"2021-06-07T14:18:45Z","title":"Proximal nested sampling for high-dimensional Bayesian model selection"},"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 2 inbound Pith citation observations for arXiv:2106.03646."}