{"as_of":"2026-08-21T22:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:eb7c864cbec5bb771a935b256baa5becc1f70dd1bcbfe645095d87233bf0bf50","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:32:52.834738Z","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":"2026-08-05T15:08:10.725611Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1807.11551","last_updated":"2019-01-17T08:39:06Z","snapshot_observed_at":"2026-08-19T16:49:29.865514Z","submitted_at":"2018-07-30T20:00:03Z","title":"Deep Recurrent Neural Networks for ECG Signal Denoising","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.11551","snapshot_observed_at":"2026-08-14T12:32:52.834738Z","title":"Deep Recurrent Neural Networks for ECG Signal Denoising,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07005","last_updated":"2019-08-19T18:09:07Z","snapshot_observed_at":"2026-08-19T19:53:57.654883Z","submitted_at":"2019-08-19T18:09:07Z","title":"On Regularization Properties of Artificial Datasets for Deep Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T12:32:52.834738Z"},"links":{"cited_paper":"/paper/1807.11551","citing_paper":"/paper/1908.07005"},"observation_digest":"sha256:00b51ffe48c1b97142c64d7dd9f334084a3daacb47869d7e171da985af94c4bb","observation_id":"8ace979b-806c-4257-baa6-3163d76ed164","resolution":{"observed_at":"2026-08-14T12:32:52.834738Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.11551","last_updated":"2019-01-17T08:39:06Z","snapshot_observed_at":"2026-08-19T16:49:29.865514Z","submitted_at":"2018-07-30T20:00:03Z","title":"Deep Recurrent Neural Networks for ECG Signal Denoising","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.11551","snapshot_observed_at":"2026-08-14T10:47:43.351275Z","title":"Detection of QRS complexes in electrocardiogram using support vector machine","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"1908.10417","last_updated":"2020-06-23T10:14:02Z","snapshot_observed_at":"2026-08-18T17:47:44.888184Z","submitted_at":"2019-08-27T19:14:32Z","title":"Complex Deep Learning Models for Denoising of Human Heart ECG signals","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T10:47:43.351275Z"},"links":{"cited_paper":"/paper/1807.11551","citing_paper":"/paper/1908.10417"},"observation_digest":"sha256:736b4f50189ac2a128966a4df2a848adee9a9c6d1e117fa56f1e3ddc54bf17c1","observation_id":"e45d541f-a28e-450d-b0d7-d439ed5fa8f5","resolution":{"observed_at":"2026-08-14T10:47:43.351275Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.11551","last_updated":"2019-01-17T08:39:06Z","snapshot_observed_at":"2026-08-19T16:49:29.865514Z","submitted_at":"2018-07-30T20:00:03Z","title":"Deep Recurrent Neural Networks for ECG Signal Denoising","version":3},"cited_work":{"arxiv_id":"1807.11551","doi":null,"metadata_source":"pith","pith_arxiv_id":"1807.11551","snapshot_observed_at":"2026-08-05T15:08:10.725611Z","title":"Deep Recurrent Neural Networks for ECG Signal Denoising","venue":"cs.NE","work_id":"e12f1812-724c-405e-9351-9002fa9ed72c","year":2018},"citing_paper":{"arxiv_id":"2508.20398","last_updated":"2025-08-28T03:51:19Z","snapshot_observed_at":"2026-08-17T11:02:39.932965Z","submitted_at":"2025-08-28T03:51:19Z","title":"TF-TransUNet1D: Time-Frequency Guided Transformer U-Net for Robust ECG Denoising in Digital Twin","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T15:08:10.625647Z"},"links":{"cited_paper":"/paper/1807.11551","citing_paper":"/paper/2508.20398"},"observation_digest":"sha256:92effae3b07fa0f55c4aee9e5259bce7187d47c11a4e509abf374de8883c970b","observation_id":"749ccfcf-01bb-4957-8762-90ee37fb3a39","resolution":{"observed_at":"2026-08-05T15:08:10.730345Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.11551","last_updated":"2019-01-17T08:39:06Z","snapshot_observed_at":"2026-08-19T16:49:29.865514Z","submitted_at":"2018-07-30T20:00:03Z","title":"Deep Recurrent Neural Networks for ECG Signal Denoising","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.11551","snapshot_observed_at":"2026-08-03T21:10:51.957449Z","title":"Deep recurrent neural networks for ECG signal denoising,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2511.16627","last_updated":"2026-08-09T04:36:49Z","snapshot_observed_at":"2026-08-17T09:16:51.386208Z","submitted_at":"2025-11-20T18:33:54Z","title":"TFCDiff: Robust ECG Denoising via Time-Frequency Complementary Diffusion","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T21:10:51.957449Z"},"links":{"cited_paper":"/paper/1807.11551","citing_paper":"/paper/2511.16627"},"observation_digest":"sha256:927f6c8f32ae756f32b7e403845cfd33e9fd196821d09aa3a22d1810635d5763","observation_id":"3f230102-92d9-4957-93e7-1112eba957c9","resolution":{"observed_at":"2026-08-03T21:10:51.957449Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1807.11551/citation-record","integrity":"/paper/1807.11551/integrity","json":"/paper/1807.11551/citation-record.json","paper":"/paper/1807.11551"},"outbound":[],"paper":{"arxiv_id":"1807.11551","last_updated":"2019-01-17T08:39:06Z","latest_version":3,"primary_category":"cs.NE","snapshot_observed_at":"2026-08-19T16:49:29.865514Z","submitted_at":"2018-07-30T20:00:03Z","title":"Deep Recurrent Neural Networks for ECG Signal Denoising"},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1807.11551."}