{"as_of":"2026-08-13T07:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0d2949a2536e0b8b3a8b072993bfb339f8676bf9d6cbd00e82ce985ff2ec535c","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T04:49:37.911065Z","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":"2026-05-21T03:33:56.402172Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2005.06534","last_updated":"2020-05-13T19:05:19Z","snapshot_observed_at":"2026-08-11T08:19:24.456009Z","submitted_at":"2020-05-13T19:05:19Z","title":"Noise Reduction in Gravitational-wave Data via Deep Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.06534","snapshot_observed_at":"2026-08-12T04:49:37.911065Z","title":"Ormiston, T","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.01058","last_updated":"2024-12-02T02:38:37Z","snapshot_observed_at":"2026-08-12T04:41:46.986148Z","submitted_at":"2024-12-02T02:38:37Z","title":"Adaptive cancellation of mains power interference in continuous gravitational wave searches with a hidden Markov model","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T04:49:37.911065Z"},"links":{"cited_paper":"/paper/2005.06534","citing_paper":"/paper/2412.01058"},"observation_digest":"sha256:7aa6e5e3fe48683ec72c5f0fa853a25eea3ea859c3303dc10670f5fe50b7ee41","observation_id":"29a240d7-0d07-423a-92c6-7aaaea81afda","resolution":{"observed_at":"2026-08-12T04:49:37.911065Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.06534","last_updated":"2020-05-13T19:05:19Z","snapshot_observed_at":"2026-08-11T08:19:24.456009Z","submitted_at":"2020-05-13T19:05:19Z","title":"Noise Reduction in Gravitational-wave Data via Deep Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.06534","snapshot_observed_at":"2026-08-10T23:54:52.009729Z","title":"Ormiston, T","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.19883","last_updated":"2024-12-27T19:00:01Z","snapshot_observed_at":"2026-08-11T08:18:28.445516Z","submitted_at":"2024-12-27T19:00:01Z","title":"A Neural Network-Based Search for Unmodeled Transients in LIGO-Virgo-KAGRA's Third Observing Run","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T23:54:52.009729Z"},"links":{"cited_paper":"/paper/2005.06534","citing_paper":"/paper/2412.19883"},"observation_digest":"sha256:109524f40cf36da031a6ecd735b9d0be5ad4062789156db0ae01f4b7593cdf1b","observation_id":"9ee39c63-62e4-4231-b853-e7af5c677b80","resolution":{"observed_at":"2026-08-10T23:54:52.009729Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.06534","last_updated":"2020-05-13T19:05:19Z","snapshot_observed_at":"2026-08-11T08:19:24.456009Z","submitted_at":"2020-05-13T19:05:19Z","title":"Noise Reduction in Gravitational-wave Data via Deep Learning","version":1},"cited_work":{"arxiv_id":"2005.06534","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2005.06534","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ormiston, T","venue":null,"work_id":"aa1da8fb-9c63-4622-9da7-a4825279e76d","year":2020},"citing_paper":{"arxiv_id":"2509.09632","last_updated":"2026-03-06T21:09:03Z","snapshot_observed_at":"2026-08-10T07:07:54.046130Z","submitted_at":"2025-09-11T17:18:31Z","title":"Nonlinear Independent Component Analysis Scheme and its application to gravitational wave data analysis","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-18T17:33:37.594218Z"},"links":{"cited_paper":"/paper/2005.06534","citing_paper":"/paper/2509.09632"},"observation_digest":"sha256:4887ddb5e585aff203ecb1b617079cfd214cd1f5a40965a797313ffabc1e4dc3","observation_id":"650be4f9-b590-4998-bfb7-1dc735f31432","resolution":{"observed_at":"2026-05-18T17:36:41.374503Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.06534","last_updated":"2020-05-13T19:05:19Z","snapshot_observed_at":"2026-08-11T08:19:24.456009Z","submitted_at":"2020-05-13T19:05:19Z","title":"Noise Reduction in Gravitational-wave Data via Deep Learning","version":1},"cited_work":{"arxiv_id":"2005.06534","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2005.06534","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ormiston, T","venue":null,"work_id":"aa1da8fb-9c63-4622-9da7-a4825279e76d","year":2020},"citing_paper":{"arxiv_id":"2511.12642","last_updated":"2026-04-20T08:04:33Z","snapshot_observed_at":"2026-08-12T21:44:51.012404Z","submitted_at":"2025-11-16T15:18:37Z","title":"Auto-encoder model for faster generation of effective one-body gravitational waveform approximations","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-17T22:06:32.129237Z"},"links":{"cited_paper":"/paper/2005.06534","citing_paper":"/paper/2511.12642"},"observation_digest":"sha256:b6d6d2592f92f9bc5c58b739a4c3d8673b4563996543d52bcc5373fd652a030e","observation_id":"b85e3577-a99f-4141-aa75-1495a79be484","resolution":{"observed_at":"2026-05-17T22:10:22.865016Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.06534","last_updated":"2020-05-13T19:05:19Z","snapshot_observed_at":"2026-08-11T08:19:24.456009Z","submitted_at":"2020-05-13T19:05:19Z","title":"Noise Reduction in Gravitational-wave Data via Deep Learning","version":1},"cited_work":{"arxiv_id":"2005.06534","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2005.06534","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ormiston, T","venue":null,"work_id":"aa1da8fb-9c63-4622-9da7-a4825279e76d","year":2020},"citing_paper":{"arxiv_id":"2605.21310","last_updated":"2026-05-20T15:37:58Z","snapshot_observed_at":"2026-08-02T18:34:09.495996Z","submitted_at":"2026-05-20T15:37:58Z","title":"Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection","version":1},"reference_index":125,"source":"pdf_text","source_observed_at":"2026-05-21T03:33:53.198336Z"},"links":{"cited_paper":"/paper/2005.06534","citing_paper":"/paper/2605.21310"},"observation_digest":"sha256:1106d21b118fff26932547ef1d723c94a61d5f130909022cca7ae81c37f8996a","observation_id":"48d378b2-f2da-4103-96a2-455ef8dbee6a","resolution":{"observed_at":"2026-05-21T03:33:56.403631Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2005.06534/citation-record","integrity":"/paper/2005.06534/integrity","json":"/paper/2005.06534/citation-record.json","paper":"/paper/2005.06534"},"outbound":[],"paper":{"arxiv_id":"2005.06534","last_updated":"2020-05-13T19:05:19Z","latest_version":1,"primary_category":"astro-ph.IM","snapshot_observed_at":"2026-08-11T08:19:24.456009Z","submitted_at":"2020-05-13T19:05:19Z","title":"Noise Reduction in Gravitational-wave Data via Deep Learning"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2005.06534."}