{"as_of":"2026-08-08T16:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2fdbac22d3a85dc4cd11250e47425d0d26d22982e2411329010fbe27743599e6","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":"2026-08-07T12:13:52.833327Z","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":"2026-08-06T16:42:15.698413Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1910.11089","last_updated":"2021-01-05T06:31:32Z","snapshot_observed_at":"2026-07-06T08:31:56.527124Z","submitted_at":"2019-10-14T09:33:26Z","title":"Real-World Image Datasets for Federated Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.11089","snapshot_observed_at":"2026-08-07T12:13:52.833327Z","title":"Real-world image datasets for federated learning","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.00379","last_updated":"2025-05-31T04:14:49Z","snapshot_observed_at":"2026-08-07T12:04:36.575072Z","submitted_at":"2025-05-31T04:14:49Z","title":"Label-shift robust federated feature screening for high-dimensional classification","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T12:13:52.833327Z"},"links":{"cited_paper":"/paper/1910.11089","citing_paper":"/paper/2506.00379"},"observation_digest":"sha256:ca4ca4f96f2195d8da8d16d4c3c13675f759b5c45ae05fb151ceff0d6ad9370a","observation_id":"e4e44b14-300b-4ea5-be97-00bf102bd814","resolution":{"observed_at":"2026-08-07T12:13:52.833327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.11089","last_updated":"2021-01-05T06:31:32Z","snapshot_observed_at":"2026-07-06T08:31:56.527124Z","submitted_at":"2019-10-14T09:33:26Z","title":"Real-World Image Datasets for Federated Learning","version":3},"cited_work":{"arxiv_id":"1910.11089","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.11089","snapshot_observed_at":"2026-08-06T16:42:15.698413Z","title":"Real-World Image Datasets for Federated Learning","venue":"cs.CV","work_id":"67e19328-763b-4c1b-bd23-887c045cbeb8","year":2019},"citing_paper":{"arxiv_id":"2507.12903","last_updated":"2025-07-17T08:42:48Z","snapshot_observed_at":"2026-08-06T16:33:03.140175Z","submitted_at":"2025-07-17T08:42:48Z","title":"Federated Learning for Commercial Image Sources","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T16:42:15.493375Z"},"links":{"cited_paper":"/paper/1910.11089","citing_paper":"/paper/2507.12903"},"observation_digest":"sha256:d5fa7833128a3780df899658104ba9d121e42309d6e749c426110501db442a87","observation_id":"07f5e7c3-064e-451b-af54-30d4910fbb0e","resolution":{"observed_at":"2026-08-06T16:42:15.702652Z","resolver_source":"local_arxiv","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/1910.11089/citation-record","integrity":"/paper/1910.11089/integrity","json":"/paper/1910.11089/citation-record.json","paper":"/paper/1910.11089"},"outbound":[],"paper":{"arxiv_id":"1910.11089","last_updated":"2021-01-05T06:31:32Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T08:31:56.527124Z","submitted_at":"2019-10-14T09:33:26Z","title":"Real-World Image Datasets for Federated Learning"},"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:1910.11089."}