{"as_of":"2026-08-08T17:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b58b8721149eb096c3a2c9fadd08bbc5e9e3020cc5a93d4d89f886d4cbd94013","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T01:06:22.225072Z","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":"2026-05-18T22:01:51.916877Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.06100","last_updated":"2025-06-11T15:48:16Z","snapshot_observed_at":"2026-08-07T03:17:18.303302Z","submitted_at":"2024-07-08T16:39:25Z","title":"Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.06100","snapshot_observed_at":"2026-08-07T01:06:22.225072Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.11987","last_updated":"2025-07-22T13:49:01Z","snapshot_observed_at":"2026-08-07T17:55:24.081351Z","submitted_at":"2025-06-13T17:46:05Z","title":"Forecast error diagnostics in neural weather models","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T01:06:22.225072Z"},"links":{"cited_paper":"/paper/2407.06100","citing_paper":"/paper/2506.11987"},"observation_digest":"sha256:d46532b672d7924a936abe186a1f2e9c958b3d0ab44f24e038a23bf288bd2951","observation_id":"dabf8b58-3d83-4397-9265-e97434154f46","resolution":{"observed_at":"2026-08-07T01:06:22.225072Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.06100","last_updated":"2025-06-11T15:48:16Z","snapshot_observed_at":"2026-08-07T03:17:18.303302Z","submitted_at":"2024-07-08T16:39:25Z","title":"Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging","version":3},"cited_work":{"arxiv_id":"2407.06100","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.06100","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2407.06100 (2024)","venue":null,"work_id":"ca7f0aa7-7278-4b06-8147-a06960c0e10a","year":2024},"citing_paper":{"arxiv_id":"2508.16168","last_updated":"2026-04-18T05:25:47Z","snapshot_observed_at":"2026-08-08T05:27:49.994240Z","submitted_at":"2025-08-22T07:43:32Z","title":"FuXi-TC: A generative framework integrating deep learning and physics-based models for improved tropical cyclone forecasts","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-18T22:01:09.117203Z"},"links":{"cited_paper":"/paper/2407.06100","citing_paper":"/paper/2508.16168"},"observation_digest":"sha256:b977f6a6eb72c5feb3f679af670a7c02f26c03963a52303701d99f20205c2144","observation_id":"c0c1cdf0-30ae-48ff-86b7-fec9cc790128","resolution":{"observed_at":"2026-05-18T22:01:51.919581Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2407.06100/citation-record","integrity":"/paper/2407.06100/integrity","json":"/paper/2407.06100/citation-record.json","paper":"/paper/2407.06100"},"outbound":[],"paper":{"arxiv_id":"2407.06100","last_updated":"2025-06-11T15:48:16Z","latest_version":3,"primary_category":"physics.ao-ph","snapshot_observed_at":"2026-08-07T03:17:18.303302Z","submitted_at":"2024-07-08T16:39:25Z","title":"Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.06100."}