{"as_of":"2026-08-12T19:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c1b71721e6f5808d7664c1dd0adc4a1cf56eeb79e154c7c6dbc470ad2753dd55","coverage":[{"denominator":7,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T04:47:57.361176Z","state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.01150/citation-record","integrity":"/paper/2412.01150/integrity","json":"/paper/2412.01150/citation-record.json","paper":"/paper/2412.01150"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1612.05560","last_updated":"2019-01-29T02:52:28Z","snapshot_observed_at":"2026-08-02T14:41:30.671146Z","submitted_at":"2016-12-16T17:14:23Z","title":"The Pan-STARRS1 Surveys","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1612.05560","snapshot_observed_at":"2026-08-12T04:47:57.322709Z","title":"et al., 2016, Proc","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2412.01150","last_updated":"2025-03-04T04:31:11Z","snapshot_observed_at":"2026-08-12T04:36:11.718958Z","submitted_at":"2024-12-02T05:48:31Z","title":"Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T04:47:57.322709Z"},"links":{"cited_paper":"/paper/1612.05560","citing_paper":"/paper/2412.01150"},"observation_digest":"sha256:a773ee920986ae1311467a824e1bb6e5ec94ab68d78c52c2ba6872bbba505464","observation_id":"eb242470-be64-4d60-a57d-f515af845b16","resolution":{"observed_at":"2026-08-12T04:47:57.322709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.08842","last_updated":"2024-11-13T18:20:29Z","snapshot_observed_at":"2026-08-10T14:41:53.143581Z","submitted_at":"2024-11-13T18:20:29Z","title":"AstroM$^3$: A self-supervised multimodal model for astronomy","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.08842","snapshot_observed_at":"2026-08-12T04:47:57.341453Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.01150","last_updated":"2025-03-04T04:31:11Z","snapshot_observed_at":"2026-08-12T04:36:11.718958Z","submitted_at":"2024-12-02T05:48:31Z","title":"Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T04:47:57.341453Z"},"links":{"cited_paper":"/paper/2411.08842","citing_paper":"/paper/2412.01150"},"observation_digest":"sha256:2198be1d8dd2b75a3c75eb9b73090bcd376e1c3b4b141953bae5a9487059fdac","observation_id":"ceb20ee6-2f2e-4b06-8333-fc177ba558e7","resolution":{"observed_at":"2026-08-12T04:47:57.341453Z","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":"2026-08-12T04:47:57.494122Z","title":null,"venue":null,"work_id":"24b340cf-4e47-4b9f-9b8b-0faa09412aa6","year":2000},"citing_paper":{"arxiv_id":"2412.01150","last_updated":"2025-03-04T04:31:11Z","snapshot_observed_at":"2026-08-12T04:36:11.718958Z","submitted_at":"2024-12-02T05:48:31Z","title":"Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T04:47:57.355706Z"},"links":{"citing_paper":"/paper/2412.01150"},"observation_digest":"sha256:f1dd53362cf99c1663c0632eaeefe55f98e700af7604ba6e9dd00324d8f94fe6","observation_id":"3d582133-e862-4333-9d02-c015be4eabfb","resolution":{"observed_at":"2026-08-12T04:47:57.498899Z","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":"2412.02527","last_updated":"2024-12-03T16:21:17Z","snapshot_observed_at":"2026-08-11T23:19:15.954723Z","submitted_at":"2024-12-03T16:21:17Z","title":"The Multimodal Universe: Enabling Large-Scale Machine Learning with 100TB of Astronomical Scientific Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.02527","snapshot_observed_at":"2026-08-12T04:47:57.349838Z","title":"III–1139 Svinkin D","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2412.01150","last_updated":"2025-03-04T04:31:11Z","snapshot_observed_at":"2026-08-12T04:36:11.718958Z","submitted_at":"2024-12-02T05:48:31Z","title":"Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T04:47:57.349838Z"},"links":{"cited_paper":"/paper/2412.02527","citing_paper":"/paper/2412.01150"},"observation_digest":"sha256:4ab04ae20a8395afe49ab7af0919febb177807522f41f0d09bc5f442e2e7e728","observation_id":"a12d2472-83c0-4d2a-9d8b-37539d86f502","resolution":{"observed_at":"2026-08-12T04:47:57.349838Z","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":"2026-08-12T04:47:57.475615Z","title":"(C3) We choose the hyperparameter combination that produces the highest value of ρDBSCAN","venue":null,"work_id":"1ac503a6-a67a-4b3a-a1c6-e27ed4c6e677","year":2025},"citing_paper":{"arxiv_id":"2412.01150","last_updated":"2025-03-04T04:31:11Z","snapshot_observed_at":"2026-08-12T04:36:11.718958Z","submitted_at":"2024-12-02T05:48:31Z","title":"Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T04:47:57.361176Z"},"links":{"citing_paper":"/paper/2412.01150"},"observation_digest":"sha256:4d324d18216052e328235f781391b4c822f7f546cbbe98e008f3d9987f4c92b3","observation_id":"47688dbc-7298-48cb-ad68-da5623547ba5","resolution":{"observed_at":"2026-08-12T04:47:57.483150Z","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":"2403.08851","last_updated":"2024-03-13T18:00:00Z","snapshot_observed_at":"2026-07-06T17:44:12.972220Z","submitted_at":"2024-03-13T18:00:00Z","title":"PAPERCLIP: Associating Astronomical Observations and Natural Language with Multi-Modal Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.08851","snapshot_observed_at":"2026-08-12T04:47:57.335716Z","title":"52 Mazets E","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2412.01150","last_updated":"2025-03-04T04:31:11Z","snapshot_observed_at":"2026-08-12T04:36:11.718958Z","submitted_at":"2024-12-02T05:48:31Z","title":"Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515","version":2},"reference_index":2011,"source":"pdf_text","source_observed_at":"2026-08-12T04:47:57.335716Z"},"links":{"cited_paper":"/paper/2403.08851","citing_paper":"/paper/2412.01150"},"observation_digest":"sha256:a71a8a7c56dee79b35b951ac211f493d4fd7808af11f298acc173319e1e40b91","observation_id":"ccca0e69-fb41-4ff0-9125-cc873fb3a5a8","resolution":{"observed_at":"2026-08-12T04:47:57.335716Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-12T04:47:57.329749Z","title":null,"venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2412.01150","last_updated":"2025-03-04T04:31:11Z","snapshot_observed_at":"2026-08-12T04:36:11.718958Z","submitted_at":"2024-12-02T05:48:31Z","title":"Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-12T04:47:57.329749Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2412.01150"},"observation_digest":"sha256:91e8c90934a7373e58142da1b76ec6c8fdab750b40d5422ef6bee69dca853459","observation_id":"736fcb4d-3408-4dc0-8478-bee213488250","resolution":{"observed_at":"2026-08-12T04:47:57.329749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.01150","last_updated":"2025-03-04T04:31:11Z","latest_version":2,"primary_category":"astro-ph.HE","snapshot_observed_at":"2026-08-12T04:36:11.718958Z","submitted_at":"2024-12-02T05:48:31Z","title":"Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515"},"reference_resolution":{"displayed":7,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":1},"total_outbound_references":7},"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 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2412.01150."}