{"as_of":"2026-08-23T09:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6ddda9e8e627ea5230e5390bd0ae946bc99cb2f5f731ea8ec83700e41f8800aa","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":"2026-08-23T06:30:58.430688+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":"2026-08-06T16:56:04.001584Z","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":"2026-05-19T21:17:48.490896Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.15705","last_updated":"2025-01-23T20:53:01Z","snapshot_observed_at":"2026-08-16T14:15:44.388359Z","submitted_at":"2024-02-24T03:44:13Z","title":"A Scalable Variational Bayes Approach to Fit High-dimensional Spatial Generalized Linear Mixed Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.15705","snapshot_observed_at":"2026-08-06T16:56:04.001584Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12251","last_updated":"2025-07-16T13:59:27Z","snapshot_observed_at":"2026-08-14T09:23:42.233049Z","submitted_at":"2025-07-16T13:59:27Z","title":"Fast Variational Bayes for Large Spatial Data","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T16:56:04.001584Z"},"links":{"cited_paper":"/paper/2402.15705","citing_paper":"/paper/2507.12251"},"observation_digest":"sha256:cc58ce9600fbd2cc2c77d82fa5010847208e7d7149435fe046f0c6df36f4b893","observation_id":"31b70b96-8e07-4c73-8494-09d33d668a3c","resolution":{"observed_at":"2026-08-06T16:56:04.001584Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.15705","last_updated":"2025-01-23T20:53:01Z","snapshot_observed_at":"2026-08-16T14:15:44.388359Z","submitted_at":"2024-02-24T03:44:13Z","title":"A Scalable Variational Bayes Approach to Fit High-dimensional Spatial Generalized Linear Mixed Models","version":3},"cited_work":{"arxiv_id":"2402.15705","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.15705","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2402.15705 , year=","venue":null,"work_id":"59d82d82-f341-4ebe-be89-0f49203c210e","year":null},"citing_paper":{"arxiv_id":"2605.16570","last_updated":"2026-05-15T19:18:39Z","snapshot_observed_at":"2026-08-15T16:05:10.009804Z","submitted_at":"2026-05-15T19:18:39Z","title":"A Cubing Strategy for Identifying Stable Hyperparameter Regions for Uncertainty Quantification in Spatial Deep Learning","version":1},"reference_index":193,"source":"arxiv_source","source_observed_at":"2026-05-19T21:14:45.344663Z"},"links":{"cited_paper":"/paper/2402.15705","citing_paper":"/paper/2605.16570"},"observation_digest":"sha256:65c6ac773566cfc2b8b1d2182f92c76e574e7ea4107fb5987c563e00c2dd9a1c","observation_id":"a8d2b97b-eb73-434d-9de9-e37c501263cb","resolution":{"observed_at":"2026-05-19T21:17:48.493916Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.15705/citation-record","integrity":"/paper/2402.15705/integrity","json":"/paper/2402.15705/citation-record.json","paper":"/paper/2402.15705"},"outbound":[],"paper":{"arxiv_id":"2402.15705","last_updated":"2025-01-23T20:53:01Z","latest_version":3,"primary_category":"stat.ME","snapshot_observed_at":"2026-08-16T14:15:44.388359Z","submitted_at":"2024-02-24T03:44:13Z","title":"A Scalable Variational Bayes Approach to Fit High-dimensional Spatial Generalized Linear Mixed 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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.15705."}