{"as_of":"2026-08-16T10:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b4172d381ad9196f042612d3fd0b9456448e07ad03e9a58d8fdbf3700ab21f65","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":"2026-08-16T06:30:59.297886+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":"2026-08-15T23:22:03.326559Z","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":"2026-08-14T13:25:35.922424Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1811.11400","last_updated":"2018-12-03T02:08:28Z","snapshot_observed_at":"2026-08-14T17:52:14.700158Z","submitted_at":"2018-11-28T06:06:38Z","title":"FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record","version":2},"cited_work":{"arxiv_id":"1811.11400","doi":null,"metadata_source":"pith","pith_arxiv_id":"1811.11400","snapshot_observed_at":"2026-08-14T13:25:35.922424Z","title":"FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record","venue":"cs.CY","work_id":"29fd63be-29ff-4f45-a9fe-51e42d83730d","year":2018},"citing_paper":{"arxiv_id":"1908.05596","last_updated":"2019-08-14T14:06:11Z","snapshot_observed_at":"2026-08-15T06:36:34.585485Z","submitted_at":"2019-08-14T14:06:11Z","title":"Two-stage Federated Phenotyping and Patient Representation Learning","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-14T13:25:35.820707Z"},"links":{"cited_paper":"/paper/1811.11400","citing_paper":"/paper/1908.05596"},"observation_digest":"sha256:b16309894860e7f91dbc633630c3172ed3a3c1adf21459dc2ab267c2c4b89cac","observation_id":"5b6d9281-efaa-4a85-b42e-1d4b7fbff210","resolution":{"observed_at":"2026-08-14T13:25:35.927179Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.11400","last_updated":"2018-12-03T02:08:28Z","snapshot_observed_at":"2026-08-14T17:52:14.700158Z","submitted_at":"2018-11-28T06:06:38Z","title":"FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.11400","snapshot_observed_at":"2026-08-15T23:22:03.326559Z","title":"Fadl: Federated- autonomous deep learning for distributed electronic health record,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04873","last_updated":"2025-05-08T01:17:15Z","snapshot_observed_at":"2026-08-15T23:17:05.350683Z","submitted_at":"2025-05-08T01:17:15Z","title":"Federated Learning for Cyber Physical Systems: A Comprehensive Survey","version":1},"reference_index":136,"source":"pdf_text","source_observed_at":"2026-08-15T23:22:03.326559Z"},"links":{"cited_paper":"/paper/1811.11400","citing_paper":"/paper/2505.04873"},"observation_digest":"sha256:75395450ee360d498b21ec17bf851951b494c49634770a64d2148dd3f252afc8","observation_id":"0a69392c-6132-449e-afdf-150146c5a014","resolution":{"observed_at":"2026-08-15T23:22:03.326559Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1811.11400/citation-record","integrity":"/paper/1811.11400/integrity","json":"/paper/1811.11400/citation-record.json","paper":"/paper/1811.11400"},"outbound":[],"paper":{"arxiv_id":"1811.11400","last_updated":"2018-12-03T02:08:28Z","latest_version":2,"primary_category":"cs.CY","snapshot_observed_at":"2026-08-14T17:52:14.700158Z","submitted_at":"2018-11-28T06:06:38Z","title":"FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record"},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1811.11400."}