{"as_of":"2026-08-07T17:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:22d064788d23976956e20f09b68a97845386da4ba5aa758845076bb26049f938","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":"2026-08-07T06:34:17.273281+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":"2026-08-06T17:29:30.233662Z","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":"2026-05-18T15:16:32.317884Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2403.10555","last_updated":"2024-03-13T06:41:37Z","snapshot_observed_at":"2026-07-06T17:45:27.526239Z","submitted_at":"2024-03-13T06:41:37Z","title":"KARINA: An Efficient Deep Learning Model for Global Weather Forecast","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.10555","snapshot_observed_at":"2026-08-06T17:29:30.233662Z","title":"Karina: An efficient deep learning model for global weather forecast","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.10893","last_updated":"2025-07-15T01:16:32Z","snapshot_observed_at":"2026-08-06T17:19:49.576310Z","submitted_at":"2025-07-15T01:16:32Z","title":"Modernizing CNN-based Weather Forecast Model towards Higher Computational Efficiency","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T17:29:30.233662Z"},"links":{"cited_paper":"/paper/2403.10555","citing_paper":"/paper/2507.10893"},"observation_digest":"sha256:7ba8794f41711835911d93b27eaefc9e60a070ea875d3867133cc7c4cb63ac9f","observation_id":"c50f18e4-87ee-4ac4-b531-09ed314a3819","resolution":{"observed_at":"2026-08-06T17:29:30.233662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.10555","last_updated":"2024-03-13T06:41:37Z","snapshot_observed_at":"2026-07-06T17:45:27.526239Z","submitted_at":"2024-03-13T06:41:37Z","title":"KARINA: An Efficient Deep Learning Model for Global Weather Forecast","version":1},"cited_work":{"arxiv_id":"2403.10555","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.10555","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"5616685c-3bf8-42eb-b5b1-2dc798df159a","year":2024},"citing_paper":{"arxiv_id":"2509.25210","last_updated":"2026-04-19T15:48:55Z","snapshot_observed_at":"2026-07-31T17:58:15.640657Z","submitted_at":"2025-09-21T05:27:52Z","title":"STCast: Adaptive Boundary Alignment for Global and Regional Weather Forecasting","version":4},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-05-18T15:13:19.854836Z"},"links":{"cited_paper":"/paper/2403.10555","citing_paper":"/paper/2509.25210"},"observation_digest":"sha256:12e4bb6a47e6676ae74dcd738f54d8479588f0e5356c2a3c0770ec95fcc1707a","observation_id":"9c18b973-32ab-4e09-a8be-9411a0e404db","resolution":{"observed_at":"2026-05-18T15:16:32.320957Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2403.10555/citation-record","integrity":"/paper/2403.10555/integrity","json":"/paper/2403.10555/citation-record.json","paper":"/paper/2403.10555"},"outbound":[],"paper":{"arxiv_id":"2403.10555","last_updated":"2024-03-13T06:41:37Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T17:45:27.526239Z","submitted_at":"2024-03-13T06:41:37Z","title":"KARINA: An Efficient Deep Learning Model 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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.10555."}