{"as_of":"2026-08-12T08:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:117e55926cd58b90b35a2fc0aba689fd1e7b82e180bb4cb738f9ddcff9c87608","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T00:06:48.844673Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T00:06:48.633994Z","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":"2026-08-11T00:06:49.310326Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"cited_work":{"arxiv_id":"2412.19683","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.19683","snapshot_observed_at":"2026-08-11T00:06:49.310326Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","venue":"gr-qc","work_id":"39a86803-c7c5-43eb-86bb-2e67550fea40","year":2024},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.633994Z"},"links":{"cited_paper":"/paper/2412.19683","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:78cc04bd93ad2391b6ac404b46ad917c79a2370f209f8d7829242d4a21b04532","observation_id":"d0efcb1f-3d96-4d11-ae96-38ca0f59e6b0","resolution":{"observed_at":"2026-08-11T00:06:49.315940Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.19683/citation-record","integrity":"/paper/2412.19683/integrity","json":"/paper/2412.19683/citation-record.json","paper":"/paper/2412.19683"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.738201Z","title":"With d degrees of freedom, it consists of • generalized coordinates qi, i= 1,","venue":null,"work_id":"63f13f15-80e0-47f1-8cf1-5f52409ea2d2","year":null},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.640512Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:fed841acd394ac7c2a687ce34ecc0f8b42f34fa37be10885e1b31aeeb15aa324","observation_id":"23516bc7-04ea-42f2-bce1-b8a14feef7db","resolution":{"observed_at":"2026-08-11T00:06:49.743527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.722367Z","title":null,"venue":null,"work_id":"01c246e7-059d-4fab-8fc7-c35c42dc9e59","year":null},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.645847Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:0fca0daae6cb008962c7f7a1ecc8bbed8b62f543358bcafc747c8adca9247256","observation_id":"a77a7786-3268-49cf-960c-421cc13c2f94","resolution":{"observed_at":"2026-08-11T00:06:49.728052Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.674159Z","title":"The initial conditions are taken along the pr = 0 line on the Poincar´ e section in r ∈ [6.36M, 6.43M ] spaced at 0.001M","venue":null,"work_id":"936a2fc3-6421-4dd2-8f4a-5eec8ebefeee","year":null},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.663002Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:0c571977f04a230cc7f58574665a4cd6a1c2d47103d977f3beed187ce86c63c1","observation_id":"6c287c97-b495-464e-96fa-e07c79c0714c","resolution":{"observed_at":"2026-08-11T00:06:49.679156Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.705907Z","title":null,"venue":null,"work_id":"7c83610c-15a5-42ea-9da5-1eb9bc4b57b7","year":null},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.652487Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:9141fe3a45ad84d9382c294a0932e9ce61103aa1eaf07a5d2702979977aed1e3","observation_id":"680daf1b-bc03-4aa6-844d-3a84812545b7","resolution":{"observed_at":"2026-08-11T00:06:49.711445Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.689674Z","title":"Knowledge of their locations will allow us to properly model the qual- itatively distinct behavior of the passage through these resonances","venue":null,"work_id":"c0e203b0-d89a-49df-a6cb-aa30869ebefb","year":null},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.657453Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:5180983e43b2501ab7b4de5ae3066e6f79d6cfe645ddf5002ce3c94f5085c760","observation_id":"220d4147-d0bd-4691-b607-4c7b8b9de37e","resolution":{"observed_at":"2026-08-11T00:06:49.695345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.568485Z","title":"Lukes-Gerakopoulos and V","venue":null,"work_id":"9badedf4-3c43-4422-813b-6b92b7f1309e","year":2021},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.716450Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:b920492dc8468635055430cbd7f95db9eb2b72fb581122e034cee2a9b2d658fc","observation_id":"0998d4da-60a7-463b-8fa9-fbf11a7102b6","resolution":{"observed_at":"2026-08-11T00:06:49.572869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.658988Z","title":"However, already in a system with 3 degrees of freedom, the Poincar´ e section becomes 4-dimensional and these simple methods are no longer applicable","venue":null,"work_id":"5674a65d-bb14-42ec-bb3d-9f14ce376b1f","year":null},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.668054Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:0f464f26fb291110b9baeef42f77c746a6cb8a91dc134c034774017660eb07d8","observation_id":"d4f33661-94c4-4e4c-8776-5546535e12b4","resolution":{"observed_at":"2026-08-11T00:06:49.663999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.644661Z","title":null,"venue":null,"work_id":"75854111-310d-4a05-bd7c-c0a6976b90ac","year":2001},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.673847Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:bb934f1513728fdbcc1a80f1d14e9eb7afeb13f5ca3196767631c25a5d4f7021","observation_id":"b12b2139-a049-410a-9745-cbb0828e788f","resolution":{"observed_at":"2026-08-11T00:06:49.649353Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"cited_work":{"arxiv_id":"2412.19683","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.19683","snapshot_observed_at":"2026-08-11T00:06:49.310326Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","venue":"gr-qc","work_id":"39a86803-c7c5-43eb-86bb-2e67550fea40","year":2024},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.633994Z"},"links":{"cited_paper":"/paper/2412.19683","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:78cc04bd93ad2391b6ac404b46ad917c79a2370f209f8d7829242d4a21b04532","observation_id":"d0efcb1f-3d96-4d11-ae96-38ca0f59e6b0","resolution":{"observed_at":"2026-08-11T00:06:49.315940Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.629038Z","title":"8 shows the result of the basic network applied to the Poincar´ e section of a test particle following a geodesic in the Johannsen-Psaltis spacetime metric (see Sec","venue":null,"work_id":"c7dd370e-d67c-4472-b62f-4a90ed9351f0","year":2001},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.678801Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:974901decbb5bd824bb4b1a40ca1b3ecb45695a70f6c466c45af3e69f983dcc0","observation_id":"d795aa53-218a-429d-9d18-d9204ef2591d","resolution":{"observed_at":"2026-08-11T00:06:49.634188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.614143Z","title":null,"venue":null,"work_id":"075edb54-787e-4273-b14c-5ca7347223fe","year":null},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.683923Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:5d0a26ccdc126673613b220296cb5687a49006c5d7b751f334228cfefac0fc1a","observation_id":"ad2fd049-1119-4699-92ef-65a0b995ffe1","resolution":{"observed_at":"2026-08-11T00:06:49.618538Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.598496Z","title":null,"venue":null,"work_id":"87bb550e-9355-41dc-9462-0393e23d09e8","year":2019},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.689116Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:b71a59a111f8a5badc68a9813271cd9d571da3c384c8824db57beb1b3859ff1b","observation_id":"d39a44cd-57ec-4ad7-bf89-6dd3dab1134b","resolution":{"observed_at":"2026-08-11T00:06:49.603977Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.10302","last_updated":"2023-03-13T09:03:14Z","snapshot_observed_at":"2026-07-06T13:23:04.941974Z","submitted_at":"2022-06-21T12:30:08Z","title":"Resonance crossing of a charged body in a magnetized Kerr background: an analogue of extreme mass ratio inspiral","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.10302","snapshot_observed_at":"2026-08-11T00:06:48.694622Z","title":"Mukherjee, O","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.694622Z"},"links":{"cited_paper":"/paper/2206.10302","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:e6520dec011c6620ac840767066e51c0c172036b93fd049085727a58473f078f","observation_id":"decf37f2-6388-40cb-be96-2de7bf7322c2","resolution":{"observed_at":"2026-08-11T00:06:48.694622Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.582464Z","title":"Zelenka, G","venue":null,"work_id":"92bed43e-3442-43ab-abcf-3274197b4464","year":2020},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.700451Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:2721abfac0284973e9f303f794e96fdf5e5637d4aa935c3e604f3990b10a09ba","observation_id":"6f4e2f6e-ede2-41c9-bf87-42f1dfab5c9d","resolution":{"observed_at":"2026-08-11T00:06:49.587445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1205.5240","last_updated":"2018-02-07T20:39:39Z","snapshot_observed_at":"2026-07-06T02:48:40.122616Z","submitted_at":"2012-05-23T18:04:13Z","title":"Relativistic Dynamics and Extreme Mass Ratio Inspirals","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1205.5240","snapshot_observed_at":"2026-08-11T00:06:48.706071Z","title":"Amaro-Seoane, Living Reviews in Relativity 21, 4 (2018), arXiv:1205.5240 [astro-ph.CO]","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.706071Z"},"links":{"cited_paper":"/paper/1205.5240","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:c7507bb920d61e8b8f221c301de5f163a06917bca9cc5e7dfe52456c653d4457","observation_id":"809cee2f-7aaf-4f26-915a-d156fda642c6","resolution":{"observed_at":"2026-08-11T00:06:48.706071Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.06016","last_updated":"2023-05-25T11:14:45Z","snapshot_observed_at":"2026-07-06T12:46:48.184877Z","submitted_at":"2022-03-11T15:38:06Z","title":"Astrophysics with the Laser Interferometer Space Antenna","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.06016","snapshot_observed_at":"2026-08-11T00:06:48.711313Z","title":"Amaro-Seoane, J","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.711313Z"},"links":{"cited_paper":"/paper/2203.06016","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:f9da7098a6151d0b862279ad63496c6df80f431341edb6bb08194f6a62b44924","observation_id":"cfd7729f-694f-441d-ae04-73a8e7858e10","resolution":{"observed_at":"2026-08-11T00:06:48.711313Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1308.4306","last_updated":"2013-08-20T13:31:55Z","snapshot_observed_at":"2026-07-06T03:21:00.544212Z","submitted_at":"2013-08-20T13:31:55Z","title":"Free motion around black holes with discs or rings: between integrability and chaos - III","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1308.4306","snapshot_observed_at":"2026-08-11T00:06:48.721516Z","title":"Sukov´ a and O","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.721516Z"},"links":{"cited_paper":"/paper/1308.4306","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:4af11448032cb6a2fd2d979d15a842be18ea31ee84899df1099fbf425699768d","observation_id":"86bc5ecb-00cc-4be9-aebc-839537de981b","resolution":{"observed_at":"2026-08-11T00:06:48.721516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:48.726536Z","title":null,"venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.726536Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:28206f64b8930d814576c32577a12ba96415b4e7895aa853ec32c7e8c287a175","observation_id":"6b567a60-4016-4c7d-8748-1a1d87087bec","resolution":{"observed_at":"2026-08-11T00:06:48.726536Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.553751Z","title":"Marwan, M","venue":null,"work_id":"a25dada4-6db3-4187-860e-934ae949a639","year":2007},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.730854Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:165985fccca021937ec783773e24aefa5fd22a5580f73bb7930938d0c6ddebf4","observation_id":"8e7484ec-faf2-4e01-a0f6-8605ba0eb179","resolution":{"observed_at":"2026-08-11T00:06:49.558483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1105.3191","last_updated":"2011-05-20T23:40:40Z","snapshot_observed_at":"2026-07-06T02:27:49.258804Z","submitted_at":"2011-05-16T20:00:02Z","title":"A Metric for Rapidly Spinning Black Holes Suitable for Strong-Field Tests of the No-Hair Theorem","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1105.3191","snapshot_observed_at":"2026-08-11T00:06:48.735513Z","title":"Johannsen and D","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.735513Z"},"links":{"cited_paper":"/paper/1105.3191","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:5f299ebb706131826f8c8ddad9c3fcee6ecde767b5ce837e86101418b09b4d3d","observation_id":"b47427bb-4db9-4724-8ee3-b8af0225cf83","resolution":{"observed_at":"2026-08-11T00:06:48.735513Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.538853Z","title":null,"venue":null,"work_id":"7053c86f-24e8-40a3-be5d-5c6cceed35b0","year":1954},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.739936Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:1dc17ddaf3b7aa98d75f0e5225b1950e3370fba76b46436cf2fb65d9d7cf3f35","observation_id":"a8241158-7f91-4d3d-a6de-fbb42129513d","resolution":{"observed_at":"2026-08-11T00:06:49.543511Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.524455Z","title":null,"venue":null,"work_id":"b9cc66c0-8184-4321-a509-0601c01bc66a","year":1963},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.744207Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:0134240bd399c61058023f7c107fb2579c4a1edb012e7f258e57ffe682bc622d","observation_id":"6240a8fd-9101-4ed3-8a5b-431a9dbdad67","resolution":{"observed_at":"2026-08-11T00:06:49.529175Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.509102Z","title":"Moser, Nachrichten der Akademie der Wissenschaften in G¨ ottingen","venue":null,"work_id":"d3475f8e-dd62-4abd-bdcd-97124a2a71ea","year":1962},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.748442Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:e686791154d1283ed731023981ccc5216fc4ac77ee7d1605f898dcf3fe09d1d8","observation_id":"8114042d-1ee5-49a4-b679-6dce0a64897c","resolution":{"observed_at":"2026-08-11T00:06:49.513879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.494104Z","title":null,"venue":null,"work_id":"6643342c-3a7d-4a13-a084-702c31c3028f","year":1913},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.753090Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:be140a95d15f067b23be721ec79bf379435d201e65d90f66c221b8923adea3ff","observation_id":"fb235b0c-8372-4c8a-9b43-0f06bd14a686","resolution":{"observed_at":"2026-08-11T00:06:49.498705Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1007.2215","last_updated":"2010-07-13T22:00:33Z","snapshot_observed_at":"2026-07-06T02:12:53.322353Z","submitted_at":"2010-07-13T22:00:33Z","title":"How to avoid potential pitfalls in recurrence plot based data analysis","version":1},"cited_work":{"arxiv_id":"1007.2215","doi":null,"metadata_source":"pith","pith_arxiv_id":"1007.2215","snapshot_observed_at":"2026-08-11T00:06:48.987139Z","title":"How to avoid potential pitfalls in recurrence plot based data analysis","venue":"nlin.CD","work_id":"a22fd4af-0dba-4014-9b87-306365e523b5","year":2010},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.757672Z"},"links":{"cited_paper":"/paper/1007.2215","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:92b04c38d5a7ce278707bc82138c8b1f996b6456c398e810a081e5edb868b0c6","observation_id":"bf78dab6-0aaf-40a0-91fb-5c8a01de0ce0","resolution":{"observed_at":"2026-08-11T00:06:48.994012Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.08446","last_updated":"2017-09-25T12:18:19Z","snapshot_observed_at":"2026-07-06T06:01:10.245241Z","submitted_at":"2017-09-25T12:18:19Z","title":"Recurrence Analysis as a tool to study chaotic dynamics of extreme mass ratio inspiral in signal with noise","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.08446","snapshot_observed_at":"2026-08-11T00:06:48.762590Z","title":"Lukes-Gerakopoulos and O","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.762590Z"},"links":{"cited_paper":"/paper/1709.08446","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:cab7571c0425ebe26230b18eadc2b910d62886b1765ca9f718163243a90b237b","observation_id":"7a5328c8-c637-4fdf-82ca-304014d156e1","resolution":{"observed_at":"2026-08-11T00:06:48.762590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1008.4650","last_updated":"2010-08-27T06:27:23Z","snapshot_observed_at":"2026-07-06T02:14:43.014311Z","submitted_at":"2010-08-27T06:27:23Z","title":"Transition from Regular to Chaotic Circulation in Magnetized Coronae near Compact Objects","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1008.4650","snapshot_observed_at":"2026-08-11T00:06:48.767417Z","title":"Kop´ aˇ cek, V","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.767417Z"},"links":{"cited_paper":"/paper/1008.4650","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:cb08d943ed46e65c1e65596df294b8c97c298a70130fa64ce02e580014dd6a4c","observation_id":"b2bb4344-5eea-4c34-ad02-0a69d502e482","resolution":{"observed_at":"2026-08-11T00:06:48.767417Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.479408Z","title":"Takens, in Dynamical Systems and Turbulence, War- wick 1980, edited by D","venue":null,"work_id":"d8090627-c9dd-461d-81a4-be1d93b74d5d","year":1980},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.772637Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:fd00464f3386de0c5497cc6ee0ba962ccb572aba08565f930efd16aa8d8c6fc7","observation_id":"6afd78a7-57a5-4f9c-92f0-ae6936c4c5c7","resolution":{"observed_at":"2026-08-11T00:06:49.484383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.463916Z","title":"Hochreiter and J","venue":null,"work_id":"9b85c8c0-ff3c-4386-9cc6-d4d0ff3b9d6a","year":1997},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.777340Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:a2bab77eda4d5af0af45a2f55dbb4b0ccc6836cfd2a716db01631b307dd72c27","observation_id":"395d7628-b97d-409d-8752-bfae383b2a58","resolution":{"observed_at":"2026-08-11T00:06:49.468975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04589","last_updated":"2024-02-07T05:17:43Z","snapshot_observed_at":"2026-08-12T06:38:52.740458Z","submitted_at":"2024-02-07T05:17:43Z","title":"Long Short-Term Memory for Early Warning Detection of Gravitational Waves","version":1},"cited_work":{"arxiv_id":"2402.04589","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.04589","snapshot_observed_at":"2026-08-11T00:06:48.929703Z","title":"Long Short-Term Memory for Early Warning Detection of Gravitational Waves","venue":"gr-qc","work_id":"62d23e65-3575-424d-92f8-cef4e61a2fad","year":2024},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.782349Z"},"links":{"cited_paper":"/paper/2402.04589","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:d2d538b341e89fc62f5c2080823a444a146ba3db4949703da57b266f7c3f240a","observation_id":"db475c41-8197-4523-a69c-80a0e2aa4b1b","resolution":{"observed_at":"2026-08-11T00:06:48.935226Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.449838Z","title":null,"venue":null,"work_id":"1b1da6a8-059f-4194-b1e2-6e568a82a1d6","year":1971},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.793967Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:80b8d5428aa474113e1fdaf920ee7973f06d27e50885a08f272b5094e3ef9e33","observation_id":"08864628-220f-474d-8995-fcdd925b02c1","resolution":{"observed_at":"2026-08-11T00:06:49.453862Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.436306Z","title":"Morbidelli, Modern celestial mechanics: aspects of solar system dynamics , 1st ed","venue":null,"work_id":"bafb4185-351e-4ec1-a482-3fe97d04709c","year":2002},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.799462Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:3f05c2432392526ba1698727d7a7e595effe6a0c3e2bb9668eebae916637934b","observation_id":"79cc8923-4dd8-4ca0-90cc-9ab5b623d66a","resolution":{"observed_at":"2026-08-11T00:06:49.440556Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.421781Z","title":"Reichl, The Transition to Chaos: Conservative Clas- sical Systems and Quantum Manifestations , Institute for Nonlinear Science (Springer, 2004)","venue":null,"work_id":"91470892-daee-4efd-8c2f-31bf36154b4b","year":2004},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.804496Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:51cc20ef420921c480f1faccaef2db99c2922521144e58dbf156100b48cd3897","observation_id":"a758e7f0-0ffa-403a-be39-939dcb2f6d25","resolution":{"observed_at":"2026-08-11T00:06:49.426531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.02442","last_updated":"2017-11-08T14:26:24Z","snapshot_observed_at":"2026-07-06T06:08:10.217657Z","submitted_at":"2017-11-07T12:45:28Z","title":"Chaotic motion in the Johannsen-Psaltis spacetime","version":2},"cited_work":{"arxiv_id":"1711.02442","doi":null,"metadata_source":"pith","pith_arxiv_id":"1711.02442","snapshot_observed_at":"2026-08-11T00:06:48.903205Z","title":"Chaotic motion in the Johannsen-Psaltis spacetime","venue":"gr-qc","work_id":"c0a33444-aab6-4ba5-bcb7-2c3791189d4c","year":2017},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.809376Z"},"links":{"cited_paper":"/paper/1711.02442","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:06f649a51535f4d8e9ef58a98a289f5d6bfb5bf305156eead578edaacc404992","observation_id":"22b39090-8601-4bd9-bcfe-0e06e1e5776e","resolution":{"observed_at":"2026-08-11T00:06:48.910738Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.407007Z","title":"Lukes-Gerakopoulos, N","venue":null,"work_id":"680edb9a-87e9-4aa8-96da-1a323bd0b97e","year":2008},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.814901Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:10e4d6db10455bb277ddd2572c5aaab61e13ce0663d1548ea0cc358abfd38615","observation_id":"345f318f-222c-41ac-94c0-4a9a9d687893","resolution":{"observed_at":"2026-08-11T00:06:49.411889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.389785Z","title":"Froeschl´ e, M","venue":null,"work_id":"3484503d-e52c-4f57-96df-da04257dcbd2","year":2005},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.820234Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:6c341e33c4fc99cc1e31eaea7a14298e056740ed84d87931684e9cac26ad4e31","observation_id":"a5587e73-d196-475d-8280-b525d9a6eb11","resolution":{"observed_at":"2026-08-11T00:06:49.395518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-11T00:06:48.825399Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.825399Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:3cf5b326df840cc2514974f6c331e9d584d608d85fc991a0b4ff5f1eff0fb25c","observation_id":"b222eadb-1480-4ece-9c5c-8db596fe775c","resolution":{"observed_at":"2026-08-11T00:06:48.825399Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.373809Z","title":"Sukov´ a, M","venue":null,"work_id":"7306032d-b059-4681-8f07-826ffdac7f0b","year":2016},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.830380Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:5e4d2f77c5a8e9bb356d3e19fb6d9d929352dae2377d7fcb9c1152033cddf4ce","observation_id":"47b87d5c-644b-4ba7-a0e0-0003bad91c1c","resolution":{"observed_at":"2026-08-11T00:06:49.378657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.358461Z","title":"Hegger, H","venue":null,"work_id":"45c80e79-89ed-4aea-b7bf-8e5bb40516e8","year":1999},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.835227Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:28cf8d9137bec8e1dced3af965314cd1cf5f9cf14b00600203702fccb503aea9","observation_id":"58b99189-6581-4172-ae08-cd48c23d0f25","resolution":{"observed_at":"2026-08-11T00:06:49.363206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.342416Z","title":"Marwan, Commandline recurrence plots (2006), https://tocsy.pik-potsdam.de/commandline-rp","venue":null,"work_id":"7803121c-ce95-4aa7-97c1-5e29472e3264","year":2006},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.840011Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:6662b50dff54ae4e5f1e838f0602aecba099ba63eb87ce108825ca39b8ace1b3","observation_id":"59880a56-da3a-4ced-85a1-98bd4b4bba16","resolution":{"observed_at":"2026-08-11T00:06:49.347559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:06:49.326988Z","title":"Marwan, Recurrence plots and cross recurrence plots (2024), http://www.recurrence-plot.tk","venue":null,"work_id":"5d050cd2-b6b9-4c8c-8467-724288c1ac3a","year":2024},"citing_paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T00:06:48.844673Z"},"links":{"citing_paper":"/paper/2412.19683"},"observation_digest":"sha256:230295984c3a29d120675d3bd0d8847d253798221495eb6cca5b39fdb0292077","observation_id":"ac0d24bf-97b3-4ebe-8684-6a0a85b45163","resolution":{"observed_at":"2026-08-11T00:06:49.332112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.19683","last_updated":"2024-12-27T15:20:57Z","latest_version":1,"primary_category":"gr-qc","snapshot_observed_at":"2026-08-11T21:55:26.888770Z","submitted_at":"2024-12-27T15:20:57Z","title":"Combining Machine Learning with Recurrence Analysis for resonance detection"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":18,"verified_exact":3,"verified_fuzzy":19},"total_outbound_references":41},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2412.19683."}