{"as_of":"2026-08-18T21:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:be3b8ba6cb9de1e4ef31c3208f5a1fb52623ab1288941bcf04419422aae80fc1","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":"2026-08-18T06:34:40.430872+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":"2026-08-15T21:56:35.449467Z","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":"2026-06-30T11:54:38.122235Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.01295","last_updated":"2024-08-16T09:26:37Z","snapshot_observed_at":"2026-08-18T08:17:39.190323Z","submitted_at":"2024-02-02T10:34:13Z","title":"ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01295","snapshot_observed_at":"2026-08-15T21:56:35.449467Z","title":"Extreme- cast: Boosting extreme value prediction for global weather forecast,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.08529","last_updated":"2025-05-13T13:02:04Z","snapshot_observed_at":"2026-08-16T22:01:20.803097Z","submitted_at":"2025-05-13T13:02:04Z","title":"ExEBench: Benchmarking Foundation Models on Extreme Earth Events","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-15T21:56:35.449467Z"},"links":{"cited_paper":"/paper/2402.01295","citing_paper":"/paper/2505.08529"},"observation_digest":"sha256:82789d7a8bf57a4e534802a926fee62f9d786d6618a188e621be5e8f5c9597ba","observation_id":"c7bbba15-800f-457f-a354-95e2e860078b","resolution":{"observed_at":"2026-08-15T21:56:35.449467Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01295","last_updated":"2024-08-16T09:26:37Z","snapshot_observed_at":"2026-08-18T08:17:39.190323Z","submitted_at":"2024-02-02T10:34:13Z","title":"ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01295","snapshot_observed_at":"2026-08-07T11:04:08.215442Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.04281","last_updated":"2026-06-24T17:14:37Z","snapshot_observed_at":"2026-08-07T22:44:46.802059Z","submitted_at":"2025-06-04T04:45:33Z","title":"Uncovering Insights of Compound Flooding with Data-Driven AI","version":3},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-07T11:04:08.215442Z"},"links":{"cited_paper":"/paper/2402.01295","citing_paper":"/paper/2506.04281"},"observation_digest":"sha256:0ddbfdca542fee95fcfce073e9d9e51d1f8bddd6d3b1af66fe7fbceb3e32f321","observation_id":"c8528434-ecde-4bc8-9299-e0de13f8b843","resolution":{"observed_at":"2026-08-07T11:04:08.215442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01295","last_updated":"2024-08-16T09:26:37Z","snapshot_observed_at":"2026-08-18T08:17:39.190323Z","submitted_at":"2024-02-02T10:34:13Z","title":"ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01295","snapshot_observed_at":"2026-08-15T18:17:52.548880Z","title":"observation","venue":null,"work_id":null,"year":1985},"citing_paper":{"arxiv_id":"2507.18378","last_updated":"2025-07-24T12:54:08Z","snapshot_observed_at":"2026-08-17T17:39:23.990297Z","submitted_at":"2025-07-24T12:54:08Z","title":"A comparison of stretched-grid and limited-area modelling for data-driven regional weather forecasting","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-15T18:17:52.548880Z"},"links":{"cited_paper":"/paper/2402.01295","citing_paper":"/paper/2507.18378"},"observation_digest":"sha256:72bcb7ee13af63d745f93b583c4230759728b33e62fcc27cf100a5b2d66c09bc","observation_id":"ebf972cd-caf6-44eb-ad41-30bc0ba4a6ff","resolution":{"observed_at":"2026-08-15T18:17:52.548880Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01295","last_updated":"2024-08-16T09:26:37Z","snapshot_observed_at":"2026-08-18T08:17:39.190323Z","submitted_at":"2024-02-02T10:34:13Z","title":"ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast","version":4},"cited_work":{"arxiv_id":"2402.01295","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.01295","snapshot_observed_at":"2026-06-30T11:54:38.122235Z","title":"Extremecast: Boosting extreme value prediction for global weather forecast.arXiv preprint arXiv:2402.01295, 2024","venue":null,"work_id":"d831d65a-2e57-40ec-bd88-21be83979946","year":2024},"citing_paper":{"arxiv_id":"2604.07928","last_updated":"2026-04-10T15:33:05Z","snapshot_observed_at":"2026-08-14T22:24:16.173135Z","submitted_at":"2026-04-09T07:47:49Z","title":"Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-10T17:58:51.295532Z"},"links":{"cited_paper":"/paper/2402.01295","citing_paper":"/paper/2604.07928"},"observation_digest":"sha256:ca556da7386a8f4a34cf54f1ae4a4b3b85fc12e80bd0434251938fbd4e0ac5e8","observation_id":"2a63ebf2-ee84-48a9-b2ff-b8c592d90093","resolution":{"observed_at":"2026-05-11T05:41:04.454065Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01295","last_updated":"2024-08-16T09:26:37Z","snapshot_observed_at":"2026-08-18T08:17:39.190323Z","submitted_at":"2024-02-02T10:34:13Z","title":"ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast","version":4},"cited_work":{"arxiv_id":"2402.01295","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.01295","snapshot_observed_at":"2026-06-30T11:54:38.122235Z","title":"Extremecast: Boosting extreme value prediction for global weather forecast.arXiv preprint arXiv:2402.01295, 2024","venue":null,"work_id":"d831d65a-2e57-40ec-bd88-21be83979946","year":2024},"citing_paper":{"arxiv_id":"2605.24945","last_updated":"2026-05-24T08:46:17Z","snapshot_observed_at":"2026-08-14T03:25:48.748310Z","submitted_at":"2026-05-24T08:46:17Z","title":"RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-06-30T11:54:05.680830Z"},"links":{"cited_paper":"/paper/2402.01295","citing_paper":"/paper/2605.24945"},"observation_digest":"sha256:1842be2c91c302faaee3f68e5c014d2e6376cfb4155384b193ec6dc040f56ada","observation_id":"fc4521b7-9a8f-43b3-b452-fddba5a3afc8","resolution":{"observed_at":"2026-06-30T11:54:38.123780Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.01295/citation-record","integrity":"/paper/2402.01295/integrity","json":"/paper/2402.01295/citation-record.json","paper":"/paper/2402.01295"},"outbound":[],"paper":{"arxiv_id":"2402.01295","last_updated":"2024-08-16T09:26:37Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T08:17:39.190323Z","submitted_at":"2024-02-02T10:34:13Z","title":"ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.01295."}