{"as_of":"2026-08-09T23:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d1a17c67a6ee34427256b926aed0b971ebccca3e35fe0a2e11ed5375d867efdb","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:49:58.793510Z","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":"2026-05-24T02:53:48.812183Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2102.06627","last_updated":"2022-01-05T17:42:51Z","snapshot_observed_at":"2026-08-08T18:30:18.513284Z","submitted_at":"2021-02-12T17:13:18Z","title":"An efficient method for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placemen","version":2},"cited_work":{"arxiv_id":"2102.06627","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2102.06627","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"9a259991-c34a-4e96-bed3-653c0e42c152","year":2021},"citing_paper":{"arxiv_id":"2403.18072","last_updated":"2025-02-02T00:33:42Z","snapshot_observed_at":"2026-07-06T17:51:36.160539Z","submitted_at":"2024-03-26T19:49:58Z","title":"Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-24T02:49:24.417674Z"},"links":{"cited_paper":"/paper/2102.06627","citing_paper":"/paper/2403.18072"},"observation_digest":"sha256:15c1c0eec3e1e238771d6dac213d42adc8e7f7e55e3c67e69239b698145ad3e4","observation_id":"3f461c3b-cb1a-4fc3-8674-a6ccff3cad2b","resolution":{"observed_at":"2026-05-24T02:53:48.815012Z","resolver_source":"arxiv_id","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"}},{"citation":{"cited_paper":{"arxiv_id":"2102.06627","last_updated":"2022-01-05T17:42:51Z","snapshot_observed_at":"2026-08-08T18:30:18.513284Z","submitted_at":"2021-02-12T17:13:18Z","title":"An efficient method for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placemen","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.06627","snapshot_observed_at":"2026-08-06T18:49:58.793510Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.07359","last_updated":"2025-07-10T00:53:57Z","snapshot_observed_at":"2026-08-08T12:50:39.167794Z","submitted_at":"2025-07-10T00:53:57Z","title":"Goal-Oriented Sequential Bayesian Experimental Design for Causal Learning","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T18:49:58.793510Z"},"links":{"cited_paper":"/paper/2102.06627","citing_paper":"/paper/2507.07359"},"observation_digest":"sha256:d96c741d3ff3dab99448003d01029ae7cb09833dac6b3c5adf160e20112328c7","observation_id":"ed5581c3-e350-4bca-8e7c-50e829048a9c","resolution":{"observed_at":"2026-08-06T18:49:58.793510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.06627","last_updated":"2022-01-05T17:42:51Z","snapshot_observed_at":"2026-08-08T18:30:18.513284Z","submitted_at":"2021-02-12T17:13:18Z","title":"An efficient method for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placemen","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.06627","snapshot_observed_at":"2026-07-13T21:02:01.705689Z","title":"An efficient method for goal- oriented linear bayesian optimal experimental design: Application to optimal sensor placemen.arXiv preprint arXiv:2102.06627, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2603.21141","last_updated":"2026-07-09T23:34:30Z","snapshot_observed_at":"2026-08-09T13:58:08.004123Z","submitted_at":"2026-03-22T09:33:15Z","title":"Tucker Tensor Train Taylor Series","version":2},"reference_index":114,"source":"pdf_text","source_observed_at":"2026-07-13T21:02:01.705689Z"},"links":{"cited_paper":"/paper/2102.06627","citing_paper":"/paper/2603.21141"},"observation_digest":"sha256:41aaee8bef578a8a997d04bb2c57d2397ccbc00bcd2579b6325e9735c47e9122","observation_id":"eb70a63a-92ea-487f-8fe4-ba3b34208b0c","resolution":{"observed_at":"2026-07-13T21:02:01.705689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2102.06627/citation-record","integrity":"/paper/2102.06627/integrity","json":"/paper/2102.06627/citation-record.json","paper":"/paper/2102.06627"},"outbound":[],"paper":{"arxiv_id":"2102.06627","last_updated":"2022-01-05T17:42:51Z","latest_version":2,"primary_category":"math.OC","snapshot_observed_at":"2026-08-08T18:30:18.513284Z","submitted_at":"2021-02-12T17:13:18Z","title":"An efficient method for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placemen"},"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 3 inbound Pith citation observations for arXiv:2102.06627."}