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Paper Citation Record · LEDGER

FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record

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.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1811.11400 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:22:03.326559Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-14T13:25:35.922424Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5b6d9281-efaa-4a85-b42e-1d4b7fbff210 · inbound

Two-stage Federated Phenotyping and Patient Representation Learning cites this paper.

Two-stage Federated Phenotyping and Patient Representation Learning FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-14T13:25:35.927179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T13:25:35.820707Z digest=sha256:d152fc4fdcfe5895f1a7fc9e97471593b2c1154ad3d8c84e14abf633f70cf54f

Observation 0a69392c-6132-449e-afdf-150146c5a014 · inbound

Federated Learning for Cyber Physical Systems: A Comprehensive Survey cites this paper.

Federated Learning for Cyber Physical Systems: A Comprehensive Survey FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record

Reference 136

Resolution
unresolved
no resolver link, observed 2026-08-15T23:22:03.326559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:22:03.326559Z digest=sha256:75395450ee360d498b21ec17bf851951b494c49634770a64d2148dd3f252afc8